Digital flood-inundation maps were created by the U.S. Geological Survey (USGS) in cooperation with the U.S. Army Corps of Engineers, New York District for a 25-mile reach of the Ottauquechee River and a 2-mile reach of Reservoir Brook in Vermont. The reach of the Ottauquechee River that was studied extends from River Road Bridge in Killington, Vt., to the Taftsville Dam in the village of Taftsville, in the town of Woodstock, Vt., and the reach of Reservoir Brook extends from a location downstream from the Woodward Reservoir in Plymouth, Vt., to its confluence with the Ottauquechee River in Bridgewater, Vt. The inundation maps depict estimates of the areal extent of flooding corresponding to the 1-percent annual exceedance probability (AEP) flood (also referred to as the 100-year flood) and the peak of the tropical storm Irene flood of August 28, 2011, which was greater than the 0.2-percent AEP flood (also referred to as the 500-year flood), as referenced to the USGS Ottauquechee River near West Bridgewater, Vt. streamgage (station 01150900).
\n\n
In addition to the two digital flood inundation maps, flood profiles were created that depict the study reach flood elevation of tropical storm Irene of August 2011 and the 10-, 2-, 1-, and 0.2-percent AEP floods, also known as the 10-, 50-, 100-, and 500-year floods, respectively. The 10-, 2-, 1-, and 0.2-percent AEP flood discharges were determined using annual peak flow data from the USGS Ottauquechee River near West Bridgewater, Vt. streamgage (station 01150900). Flood profiles were computed for the Ottauquechee River and Reservoir Brook by means of a one-dimensional step-backwater model. The model was calibrated using documented high-water marks of the peak of the tropical storm Irene flood of August 2011 as well as stage discharge data as determined for USGS Ottauquechee River near West Bridgewater, Vt. streamgage (station 01150900). The simulated water-surface profiles were combined with a digital elevation model within a geographic information system to delineate the areas flooded during tropical storm Irene and for the 1-percent AEP water-surface profile. The digital elevation model data were derived from light detection and ranging (lidar) data obtained for a 3,281-foot (1,000-meter) corridor along the Ottauquechee River study reach and were augmented with 33-foot (10- meter) contour interval data in the modeled flood-inundation areas outside the lidar corridor. The 33-foot (10-meter) contour interval USGS 15-minute quadrangle topographic digital raster graphics map used to augment lidar data was produced at a scale of 1:24,000. The digital flood inundation maps and flood profiles along with information regarding current stage from USGS streamgages on the Internet provide emergency management personnel and residents with information that is critical for flood response activities, such as evacuations and road closures, as well as for post-flood recovery efforts.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20145214","collaboration":"Prepared in cooperation with the U.S. Army Corps of Engineers","usgsCitation":"Flynn, R.H., 2014, Analysis of floods, including the tropical storm Irene inundation, of the Ottauquechee River in Woodstock, Bridgewater, and Killington and of Reservoir Brook in Bridgewater and Plymouth, Vermont: U.S. Geological Survey Scientific Investigations Report 2014-5214, Report: vii, 11 p.; Readme; 5 Appendixes, https://doi.org/10.3133/sir20145214.","productDescription":"Report: vii, 11 p.; Readme; 5 Appendixes","numberOfPages":"25","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-055865","costCenters":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"links":[{"id":296815,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir20145214.jpg"},{"id":296807,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2014/5214/"},{"id":296808,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2014/5214/pdf/sir2014-5214.pdf","size":"2.25 MB","linkFileType":{"id":1,"text":"pdf"}},{"id":296809,"rank":3,"type":{"id":20,"text":"Read Me"},"url":"https://pubs.usgs.gov/sir/2014/5214/appendix/sir2014-5214_app-readme.txt","text":"Appendix 1-5 Readme","size":"14 kB"},{"id":296810,"rank":4,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2014/5214/appendix/sir2014-5214_apend01.pdf","text":"Appendix 1","size":"7.71 MB","linkFileType":{"id":1,"text":"pdf"}},{"id":296811,"rank":5,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2014/5214/appendix/sir2014-5214_apend02.pdf","text":"Appendix 2","size":"172 MB","linkFileType":{"id":1,"text":"pdf"}},{"id":296812,"rank":6,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2014/5214/appendix/sir2014-5214_apend03.pdf","text":"Appendix 3","size":"140 kB","linkFileType":{"id":1,"text":"pdf"}},{"id":296813,"rank":7,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2014/5214/appendix/sir2014-5214_apend04.pdf","text":"Appendix 4","size":"59 kB","linkFileType":{"id":1,"text":"pdf"}},{"id":296814,"rank":8,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2014/5214/appendix/sir2014-5214_apend05.pdf","text":"Appendix 5","size":"55.3 kB","linkFileType":{"id":1,"text":"pdf"}}],"country":"United States","state":"Vermont","otherGeospatial":"Ottauquechee River, Reservoir Brook","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -72.74871826171875,\n 43.511708955963776\n ],\n [\n -72.74871826171875,\n 43.7572088788494\n ],\n [\n -72.23236083984375,\n 43.7572088788494\n ],\n [\n -72.23236083984375,\n 43.511708955963776\n ],\n [\n -72.74871826171875,\n 43.511708955963776\n ]\n ]\n ]\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"54dd2a54e4b08de9379b2fe6","contributors":{"authors":[{"text":"Flynn, Robert H. rflynn@usgs.gov","contributorId":2137,"corporation":false,"usgs":true,"family":"Flynn","given":"Robert","email":"rflynn@usgs.gov","middleInitial":"H.","affiliations":[{"id":405,"text":"NH/VT office of New England Water Science Center","active":true,"usgs":true}],"preferred":true,"id":525746,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70135050,"text":"70135050 - 2014 - Understanding the magnitude dependence of PGA and PGV in NGA-West 2 data","interactions":[],"lastModifiedDate":"2017-05-16T10:54:45","indexId":"70135050","displayToPublicDate":"2014-12-18T11:15:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1135,"text":"Bulletin of the Seismological Society of America","onlineIssn":"1943-3573","printIssn":"0037-1106","active":true,"publicationSubtype":{"id":10}},"title":"Understanding the magnitude dependence of PGA and PGV in NGA-West 2 data","docAbstract":"The Next Generation Attenuation‐West 2 (NGA‐West 2) 2014 ground‐motion prediction equations (GMPEs) model ground motions as a function of magnitude and distance, using empirically derived coefficients (e.g., Bozorgniaet al., 2014); as such, these GMPEs do not clearly employ earthquake source parameters beyond moment magnitude (M) and focal mechanism. To better understand the magnitude‐dependent trends in the GMPEs, we build a comprehensive earthquake source‐based model to explain the magnitude dependence of peak ground acceleration and peak ground velocity in the NGA‐West 2 ground‐motion databases and GMPEs. Our model employs existing models (Hanks and McGuire, 1981; Boore, 1983, 1986; Anderson and Hough, 1984) that incorporate a point‐source Brune model, including a constant stress drop and the high‐frequency attenuation parameter κ0, random vibration theory, and a finite‐fault assumption at the large magnitudes to describe the data from magnitudes 3 to 8. We partition this range into four different magnitude regions, each of which has different functional dependences on M. Use of the four magnitude partitions separately allows greater understanding of what happens in any one subrange, as well as the limiting conditions between the subranges. This model provides a remarkably good fit to the NGA data for magnitudes from 3<M<8 at close rupture distances (Rrup≤20 km). We explore the trade‐offs between Δσ and κ0 in ground‐motion models and data, which play an important role in understanding small‐magnitude data, for which the corner frequency is masked by the attenuation of high frequencies. That this simple, source‐based model matches the NGA‐West 2 GMPEs and data so well suggests that considerable simplicity underlies the parametrically complex NGA GMPEs.
","language":"English","publisher":"Seismological Society of America","doi":"10.1785/0120130283","usgsCitation":"Baltay Sundstrom, A.S., and Hanks, T.C., 2014, Understanding the magnitude dependence of PGA and PGV in NGA-West 2 data: Bulletin of the Seismological Society of America, v. 104, no. 6, p. 2851-2865, https://doi.org/10.1785/0120130283.","productDescription":"15 p.","startPage":"2851","endPage":"2865","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-052324","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":296788,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"104","issue":"6","noUsgsAuthors":false,"publicationDate":"2014-10-21","publicationStatus":"PW","scienceBaseUri":"54dd2ac6e4b08de9379b31fb","contributors":{"authors":[{"text":"Baltay Sundstrom, Annemarie S. 0000-0002-6514-852X abaltay@usgs.gov","orcid":"https://orcid.org/0000-0002-6514-852X","contributorId":4932,"corporation":false,"usgs":true,"family":"Baltay Sundstrom","given":"Annemarie","email":"abaltay@usgs.gov","middleInitial":"S.","affiliations":[{"id":234,"text":"Earthquake Hazards Program","active":true,"usgs":true},{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":526749,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hanks, Thomas C. 0000-0003-0928-0056 thanks@usgs.gov","orcid":"https://orcid.org/0000-0003-0928-0056","contributorId":3065,"corporation":false,"usgs":true,"family":"Hanks","given":"Thomas","email":"thanks@usgs.gov","middleInitial":"C.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":526750,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70135868,"text":"70135868 - 2014 - River chloride trends in snow-affected urban watersheds: increasing concentrations outpace urban growth rate and are common among all seasons","interactions":[],"lastModifiedDate":"2014-12-18T10:06:50","indexId":"70135868","displayToPublicDate":"2014-12-18T10:00:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3352,"text":"Science of the Total Environment","active":true,"publicationSubtype":{"id":10}},"title":"River chloride trends in snow-affected urban watersheds: increasing concentrations outpace urban growth rate and are common among all seasons","docAbstract":"Chloride concentrations in northern U.S. included in this study have increased substantially over time with average concentrations approximately doubling from 1990 to 2011, outpacing the rate of urbanization in the northern U.S. Historical data were examined for 30 monitoring sites on 19 streams that had chloride concentration and flow records of 18 to 49 years. Chloride concentrations in most studied streams increased in all seasons (13 of 19 in all seasons; 16 of 19 during winter); maximum concentrations occurred during winter. Increasing concentrations during non-deicing periods suggest that chloride was stored in hydrologic reservoirs, such as the shallow groundwater system, during the winter and slowly released in baseflow throughout the year. Streamflow dependency was also observed with chloride concentrations increasing as streamflow decreased, a result of dilution during rainfall- and snowmelt-induced high-flow periods. The influence of chloride on aquatic life increased with time; 29% of sites studied exceeded the concentration for the USEPA chronic water quality criteria of 230 mg/L by an average of more than 100 individual days per year during 2006–2011. The rapid rate of chloride concentration increase in these streams is likely due to a combination of possible increased road salt application rates, increased baseline concentrations, and greater snowfall in the Midwestern U.S. during the latter portion of the study period.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.scitotenv.2014.12.012","usgsCitation":"Corsi, S., De Cicco, L., Lutz, M., and Hirsch, R.M., 2014, River chloride trends in snow-affected urban watersheds: increasing concentrations outpace urban growth rate and are common among all seasons: Science of the Total Environment, v. 508, p. 488-497, https://doi.org/10.1016/j.scitotenv.2014.12.012.","productDescription":"10 p.","startPage":"488","endPage":"497","numberOfPages":"10","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-061255","costCenters":[{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true}],"links":[{"id":472572,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.scitotenv.2014.12.012","text":"Publisher Index Page"},{"id":296782,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"projection":"Albers Equal Area Conic USGS CONUS Projection","datum":"North American Datum of 1983","country":"United States","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -123.26660156249999,\n 42.58544425738491\n ],\n [\n -123.26660156249999,\n 45.9511496866914\n ],\n [\n -119.53125,\n 45.9511496866914\n ],\n [\n -119.53125,\n 42.58544425738491\n ],\n [\n -123.26660156249999,\n 42.58544425738491\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -104.853515625,\n 38.95940879245423\n ],\n [\n -104.853515625,\n 39.791654835253425\n ],\n [\n -104.17236328125,\n 39.791654835253425\n ],\n [\n -104.17236328125,\n 38.95940879245423\n ],\n [\n -104.853515625,\n 38.95940879245423\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -98.89892578125,\n 32.26855544621479\n ],\n [\n -98.89892578125,\n 34.125447565116126\n ],\n [\n -96.30615234375,\n 34.125447565116126\n ],\n [\n -96.30615234375,\n 32.26855544621479\n ],\n [\n -98.89892578125,\n 32.26855544621479\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -89.3408203125,\n 44.715513732021336\n ],\n [\n -89.3408203125,\n 45.82879925192134\n ],\n [\n -87.56103515625,\n 45.82879925192134\n ],\n [\n -87.56103515625,\n 44.715513732021336\n ],\n [\n -89.3408203125,\n 44.715513732021336\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -89.3408203125,\n 41.918628865183045\n ],\n [\n -89.3408203125,\n 44.134913443750726\n ],\n [\n -87.47314453125,\n 44.134913443750726\n ],\n [\n -87.47314453125,\n 41.918628865183045\n ],\n [\n -89.3408203125,\n 41.918628865183045\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -83.84765625,\n 42.293564192170095\n ],\n [\n -83.84765625,\n 43.08493742707592\n ],\n [\n -82.7490234375,\n 43.08493742707592\n ],\n [\n -82.7490234375,\n 42.293564192170095\n ],\n [\n -83.84765625,\n 42.293564192170095\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -81.650390625,\n 41.1290213474951\n ],\n [\n -81.650390625,\n 41.77131167976407\n ],\n [\n -80.595703125,\n 41.77131167976407\n ],\n [\n -80.595703125,\n 41.1290213474951\n ],\n [\n -81.650390625,\n 41.1290213474951\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -79.65087890624999,\n 37.84015683604134\n ],\n [\n -79.65087890624999,\n 40.94671366508002\n ],\n [\n -74.970703125,\n 40.94671366508002\n ],\n [\n -74.970703125,\n 37.84015683604134\n ],\n [\n -79.65087890624999,\n 37.84015683604134\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"508","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"54dd2aabe4b08de9379b3173","chorus":{"doi":"10.1016/j.scitotenv.2014.12.012","url":"http://dx.doi.org/10.1016/j.scitotenv.2014.12.012","publisher":"Elsevier BV","authors":"Corsi Steven R., De Cicco Laura A., Lutz Michelle A., Hirsch Robert M.","journalName":"Science of The Total Environment","publicationDate":"3/2015","auditedOn":"1/16/2015","publiclyAccessibleDate":"12/5/2014"},"contributors":{"authors":[{"text":"Corsi, Steven R. srcorsi@usgs.gov","contributorId":131018,"corporation":false,"usgs":true,"family":"Corsi","given":"Steven R.","email":"srcorsi@usgs.gov","affiliations":[{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true}],"preferred":false,"id":536944,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"De Cicco, Laura A. 0000-0002-3915-9487 ldecicco@usgs.gov","orcid":"https://orcid.org/0000-0002-3915-9487","contributorId":4814,"corporation":false,"usgs":true,"family":"De Cicco","given":"Laura A.","email":"ldecicco@usgs.gov","affiliations":[{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true}],"preferred":false,"id":536945,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Lutz, Michelle A. malutz@usgs.gov","contributorId":1839,"corporation":false,"usgs":true,"family":"Lutz","given":"Michelle A.","email":"malutz@usgs.gov","affiliations":[{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true}],"preferred":false,"id":536946,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hirsch, Robert M. 0000-0002-4534-075X rhirsch@usgs.gov","orcid":"https://orcid.org/0000-0002-4534-075X","contributorId":2005,"corporation":false,"usgs":true,"family":"Hirsch","given":"Robert","email":"rhirsch@usgs.gov","middleInitial":"M.","affiliations":[{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true},{"id":37316,"text":"WMA - Integrated Information Dissemination Division","active":true,"usgs":true},{"id":502,"text":"Office of Surface Water","active":true,"usgs":true},{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true}],"preferred":true,"id":536947,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70171444,"text":"70171444 - 2014 - Impacts of mountaintop mining on terrestrial ecosystem integrity: Identifying landscape thresholds for avian species in the central Appalachians, United States","interactions":[],"lastModifiedDate":"2016-06-01T11:41:05","indexId":"70171444","displayToPublicDate":"2014-12-18T02:30:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2602,"text":"Landscape Ecology","active":true,"publicationSubtype":{"id":10}},"title":"Impacts of mountaintop mining on terrestrial ecosystem integrity: Identifying landscape thresholds for avian species in the central Appalachians, United States","docAbstract":"Mountaintop removal/valley fill (MTR/VF) mining in the central Appalachians is a major driver of landscape change within terrestrial ecosystems.
\nWe quantified avian community and individual taxa thresholds in response to changing landscapes from MTR/VF using a Threshold Indicator Taxa Analysis approach.
\nWe conducted 50-m fixed radius avian surveys (n = 707) within forest adjacent to mine lands in 2012–2013 and obtained data for additional surveys (n = 905) sampled using comparable methods during 2008–2013. We quantified positive and negative community, habitat guild, and species thresholds in abundance and occurrence for each of five landscape metrics within a 1-km radius of each survey point.
\nReclaimed mine-dominated landscapes (less forest and more grassland/shrubland cover) elicited more negative (57 %) than positive (39 %) species responses. Negative thresholds for each landscape metric generally occurred at lower values than positive thresholds, thus negatively responding species were detrimentally affected before positively responding species benefitted. Forest interior birds generally responded negatively to landscape metric thresholds, interior edge species responses were mixed, and early successional birds responded positively. The forest interior guild declined most at 4 % forest loss, while the shrubland guild increased greatest after 52 % loss. Based on random forest importance ranks, total amount of landscape grassland/shrubland had the most influence, although this varied by guild.
\nBecause of little overlap in habitat requirements, managing landscapes simultaneously to maximally benefit both guilds may not be possible. Our avian thresholds identify single community management targets accounting for scarce species. Guild or individual species thresholds allow for species-specific management.
\nIn July 2011, the U.S. Geological Survey, in cooperation with the U.S. Army Corps of Engineers, completed a geophysical survey using electrical resistivity along an approximately 6-mile reach of the lower American River in Sacramento, California, to map near-surface lithological variations. This survey is a part of a manifold and comprehensive study of river-flow dynamics and geologic boundary-property knowledge necessary to estimate scour potential and levee erosion risk. Data were acquired on the left (south or west) bank between river mile 5 and 10.7 as well as a short section on the right bank from river mile 5.4 to 6. Thirteen direct-current resistivity profiles and approximately 8.3 miles of capacitively coupled resisistivity data were acquired along accessible areas of the floodplain between the levee and river bank. Capacitively coupled resistivity was used as a reconnaissance tool, because it allowed for greater spatial coverage of data but with lower resolution and depth of investigation than the DC resistivity method. The study area contains Pleistocene-age alluvial deposits, dominated by gravels, sands, silts, and clays, that vary in both lateral extent and depth. Several generations of lithologic logs were used to help interpret resistivity variations observed in the resistivity models.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20141242","collaboration":"Prepared in cooperation with the U.S. Army Corps of Engineers","usgsCitation":"Burton, B.L., Powers, M.H., and Ball, L.B., 2014, Characterization of subsurface stratigraphy along the lower American River floodplain using electrical resistivity, Sacramento, California, 2011: U.S. Geological Survey Open-File Report 2014-1242, Report: iv, 62 p.; Direct-current resistivity data; Capacitively coupled resistivity data, https://doi.org/10.3133/ofr20141242.","productDescription":"Report: iv, 62 p.; Direct-current resistivity data; Capacitively coupled resistivity data","numberOfPages":"66","onlineOnly":"N","additionalOnlineFiles":"Y","ipdsId":"IP-055799","costCenters":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"links":[{"id":296766,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr20141242.jpg"},{"id":296763,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2014/1242/pdf/ofr2014-1242.pdf","text":"Report","size":"19.4 MB","linkFileType":{"id":1,"text":"pdf"},"description":"Report"},{"id":296764,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/of/2014/1242/App3/AmRiv_DCres_stg.zip","text":"Direct-current resistivity data","size":"592 kB","description":"Digital Data"},{"id":296762,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2014/1242/","text":"Index Page","linkFileType":{"id":5,"text":"html"}},{"id":296765,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/of/2014/1242/App3/AmRiv_CCres_BIN.zip","text":"Capacitively coupled resistivity data","size":"284 kB","description":"Digital Data"}],"projection":"California State Plane projection, zone 2","datum":"North American Datum of 1983","country":"United States","state":"California","city":"Sacramento","otherGeospatial":"American River","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5492a92ee4b00eda8915acf3","contributors":{"authors":[{"text":"Burton, Bethany L. 0000-0001-5011-7862 blburton@usgs.gov","orcid":"https://orcid.org/0000-0001-5011-7862","contributorId":138925,"corporation":false,"usgs":true,"family":"Burton","given":"Bethany","email":"blburton@usgs.gov","middleInitial":"L.","affiliations":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":758621,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Powers, Michael H. 0000-0002-4480-7856 mhpowers@usgs.gov","orcid":"https://orcid.org/0000-0002-4480-7856","contributorId":851,"corporation":false,"usgs":true,"family":"Powers","given":"Michael","email":"mhpowers@usgs.gov","middleInitial":"H.","affiliations":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":536902,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ball, Lyndsay B. 0000-0002-6356-4693 lbball@usgs.gov","orcid":"https://orcid.org/0000-0002-6356-4693","contributorId":1138,"corporation":false,"usgs":true,"family":"Ball","given":"Lyndsay","email":"lbball@usgs.gov","middleInitial":"B.","affiliations":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":536903,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70134073,"text":"ofr20141199 - 2014 - Geologic map of the Ahankashan-Rakhna basin, Badghis, Ghor, and Herat Provinces, Afghanistan, modified from the 1974 original map compilation of Y.I. Shcherbina and others","interactions":[],"lastModifiedDate":"2014-12-17T09:41:37","indexId":"ofr20141199","displayToPublicDate":"2014-12-17T10:30:00","publicationYear":"2014","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2014-1199","title":"Geologic map of the Ahankashan-Rakhna basin, Badghis, Ghor, and Herat Provinces, Afghanistan, modified from the 1974 original map compilation of Y.I. Shcherbina and others","docAbstract":"This geologic map of the Ahankashan-Rakhna basin, Afghanistan, is a redrafted and modified version of the Geological map of the area of Ahankashan-Rakhna basin, scale 1:50,000 and Geological map of the Ahankashan area with data on mineral resources, scale 1:12,000 from Shcherbina and others (1974) (Soviet report no. 0822). That unpublished Soviet report contains the original maps and cross sections, which were prepared in cooperation with the Ministry of Mines and Industries of the Republic of Afghanistan in Kabul during 1974 under contract no. 50728 (Technoexport, USSR). The redrafted maps and cross sections in this USGS publication illustrate the geology of the Ahankashan and Rakhna basins, located within Badghis, Ghor, and Herat Provinces.
\n\n
The Ahankashan and Rakhna prospect area is one of several gold and copper deposits within west-central Afghanistan. Here, various felsic to intermediate igneous porphyries intrude Lower Triassic to lower Paleogene sedimentary rocks, producing mineral and ore-bearing zones related to hydrothermal alteration, skarns, silicification, and crushing (brecciation). Mineralized skarns contain assemblages such as magnetite, magnetite-hematite, epidote-hematite, and epidote-garnet, as well as disseminations of chalcopyrite, covellite, chalcocite, cuprite, malachite, and azurite. Gold mineralization is mainly associated with zones of crushing along faults, and with small silicified igneous veins within granite and quartz porphyry.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20141199","collaboration":"Prepared in cooperation with the Afghan Geological Survey under the auspices of the U.S. Department of Defense","usgsCitation":"Tucker, R.D., Stettner, W.R., Masonic, L., and Bogdanow, A.K., 2014, Geologic map of the Ahankashan-Rakhna basin, Badghis, Ghor, and Herat Provinces, Afghanistan, modified from the 1974 original map compilation of Y.I. Shcherbina and others: U.S. Geological Survey Open-File Report 2014-1199, Report: 51.00 x 41.00 inches, https://doi.org/10.3133/ofr20141199.","productDescription":"Report: 51.00 x 41.00 inches","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-056911","costCenters":[{"id":497,"text":"Office of International Programs","active":false,"usgs":true}],"links":[{"id":296743,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr20141199.jpg"},{"id":296739,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2014/1199/"},{"id":296740,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2014/1199/pdf/ofr2014-1199.pdf","size":"76.5 MB","linkFileType":{"id":1,"text":"pdf"}}],"scale":"500000","projection":"Universal Transverse Mercator projection","datum":"World Geodetic System 1984 Datum","country":"Afghanistan","state":"Badghis, Ghor, Herat","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n 63.369140625,\n 33.797408767572485\n ],\n [\n 63.369140625,\n 35.371135022800985\n ],\n [\n 65.58837890625,\n 35.371135022800985\n ],\n [\n 65.58837890625,\n 33.797408767572485\n ],\n [\n 63.369140625,\n 33.797408767572485\n ]\n ]\n ]\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5492a936e4b00eda8915acfd","contributors":{"authors":[{"text":"Tucker, Robert D. 0000-0001-8463-4358 rtucker@usgs.gov","orcid":"https://orcid.org/0000-0001-8463-4358","contributorId":2007,"corporation":false,"usgs":true,"family":"Tucker","given":"Robert","email":"rtucker@usgs.gov","middleInitial":"D.","affiliations":[{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true}],"preferred":true,"id":525677,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Stettner, Will R. wstettne@usgs.gov","contributorId":4021,"corporation":false,"usgs":true,"family":"Stettner","given":"Will","email":"wstettne@usgs.gov","middleInitial":"R.","affiliations":[{"id":6676,"text":"USGS (retired)","active":true,"usgs":false}],"preferred":true,"id":525678,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Masonic, Linda M. lmasonic@usgs.gov","contributorId":1418,"corporation":false,"usgs":true,"family":"Masonic","given":"Linda M.","email":"lmasonic@usgs.gov","affiliations":[{"id":5072,"text":"Office of Communication and Publishing","active":true,"usgs":true}],"preferred":false,"id":525679,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Bogdanow, Anya K. abogdanow@usgs.gov","contributorId":5406,"corporation":false,"usgs":true,"family":"Bogdanow","given":"Anya","email":"abogdanow@usgs.gov","middleInitial":"K.","affiliations":[{"id":245,"text":"Eastern Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":false,"id":525680,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70135738,"text":"70135738 - 2014 - Effects of capturing and collaring on polar bears: findings from long-term research on the southern Beaufort Sea population","interactions":[],"lastModifiedDate":"2018-08-19T21:52:56","indexId":"70135738","displayToPublicDate":"2014-12-17T10:15:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3777,"text":"Wildlife Research","active":true,"publicationSubtype":{"id":10}},"title":"Effects of capturing and collaring on polar bears: findings from long-term research on the southern Beaufort Sea population","docAbstract":"Context: The potential for research methods to affect wildlife is an increasing concern among both scientists and the public. This topic has a particular urgency for polar bears because additional research is needed to monitor and understand population responses to rapid loss of sea ice habitat.
Aims: This study used data collected from polar bears sampled in the Alaska portion of the southern Beaufort Sea to investigate the potential for capture to adversely affect behaviour and vital rates. We evaluated the extent to which capture, collaring and handling may influence activity and movement days to weeks post-capture, and body mass, body condition, reproduction and survival over 6 months or more.
Methods: We compared post-capture activity and movement rates, and relationships between prior capture history and body mass, body condition and reproductive success. We also summarised data on capture-related mortality.
Key results: Individual-based estimates of activity and movement rates reached near-normal levels within 2–3 days and fully normal levels within 5 days post-capture. Models of activity and movement rates among all bears had poor fit, but suggested potential for prolonged, lower-level rate reductions. Repeated captures was not related to negative effects on body condition, reproduction or cub growth or survival. Capture-related mortality was substantially reduced after 1986, when immobilisation drugs were changed, with only 3 mortalities in 2517 captures from 1987–2013.
Conclusions: Polar bears in the southern Beaufort Sea exhibited the greatest reductions in activity and movement rates 3.5 days post-capture. These shorter-term, post-capture effects do not appear to have translated into any long-term effects on body condition, reproduction, or cub survival. Additionally, collaring had no effect on polar bear recovery rates, body condition, reproduction or cub survival.
Implications: This study provides empirical evidence that current capture-based research methods do not have long-term implications, and are not contributing to observed changes in body condition, reproduction or survival in the southern Beaufort Sea. Continued refinement of capture protocols, such as the use of low-impact dart rifles and reversible drug combinations, might improve polar bear response to capture and abate short-term reductions in activity and movement post-capture.
","language":"English","publisher":"Csiro Publishing","doi":"10.1071/WR13225","usgsCitation":"Rode, K.D., Pagano, A.M., Bromaghin, J.F., Atwood, T.C., Durner, G.M., Simac, K.S., and Amstrup, S.C., 2014, Effects of capturing and collaring on polar bears: findings from long-term research on the southern Beaufort Sea population: Wildlife Research, v. 41, no. 4, p. 311-322, https://doi.org/10.1071/WR13225.","productDescription":"12 p.","startPage":"311","endPage":"322","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-053304","costCenters":[{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true}],"links":[{"id":296741,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"otherGeospatial":"Beaufort Sea","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -154.3359375,\n 74.4964131169431\n ],\n [\n -123.662109375,\n 74.56673621013677\n ],\n [\n -127.529296875,\n 69.83962194067463\n ],\n [\n -136.7578125,\n 69.00567519658819\n ],\n [\n -157.5,\n 71.27259471233448\n ],\n [\n -154.3359375,\n 74.4964131169431\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"41","issue":"4","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5492a931e4b00eda8915acf7","contributors":{"authors":[{"text":"Rode, Karyn D. 0000-0002-3328-8202 krode@usgs.gov","orcid":"https://orcid.org/0000-0002-3328-8202","contributorId":5053,"corporation":false,"usgs":true,"family":"Rode","given":"Karyn","email":"krode@usgs.gov","middleInitial":"D.","affiliations":[{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":536771,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Pagano, Anthony M. 0000-0003-2176-0909 apagano@usgs.gov","orcid":"https://orcid.org/0000-0003-2176-0909","contributorId":3884,"corporation":false,"usgs":true,"family":"Pagano","given":"Anthony","email":"apagano@usgs.gov","middleInitial":"M.","affiliations":[{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true}],"preferred":true,"id":536861,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bromaghin, Jeffrey F. 0000-0002-7209-9500 jbromaghin@usgs.gov","orcid":"https://orcid.org/0000-0002-7209-9500","contributorId":139899,"corporation":false,"usgs":true,"family":"Bromaghin","given":"Jeffrey","email":"jbromaghin@usgs.gov","middleInitial":"F.","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true}],"preferred":true,"id":536862,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Atwood, Todd C. 0000-0002-1971-3110 tatwood@usgs.gov","orcid":"https://orcid.org/0000-0002-1971-3110","contributorId":4368,"corporation":false,"usgs":true,"family":"Atwood","given":"Todd","email":"tatwood@usgs.gov","middleInitial":"C.","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true}],"preferred":true,"id":536863,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Durner, George M. 0000-0002-3370-1191 gdurner@usgs.gov","orcid":"https://orcid.org/0000-0002-3370-1191","contributorId":3576,"corporation":false,"usgs":true,"family":"Durner","given":"George","email":"gdurner@usgs.gov","middleInitial":"M.","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true}],"preferred":true,"id":536864,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Simac, Kristin S. 0000-0002-4072-1940 ksimac@usgs.gov","orcid":"https://orcid.org/0000-0002-4072-1940","contributorId":131096,"corporation":false,"usgs":true,"family":"Simac","given":"Kristin","email":"ksimac@usgs.gov","middleInitial":"S.","affiliations":[{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true}],"preferred":true,"id":536865,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Amstrup, Steven C.","contributorId":67034,"corporation":false,"usgs":false,"family":"Amstrup","given":"Steven","email":"","middleInitial":"C.","affiliations":[{"id":13182,"text":"Polar Bears International","active":true,"usgs":false}],"preferred":false,"id":536866,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70160769,"text":"70160769 - 2014 - Efficacy of iodine for disinfection of Lake Sturgeon eggs from the St. Lawrence River, New York","interactions":[],"lastModifiedDate":"2015-12-30T14:36:17","indexId":"70160769","displayToPublicDate":"2014-12-16T15:30:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2885,"text":"North American Journal of Aquaculture","active":true,"publicationSubtype":{"id":10}},"title":"Efficacy of iodine for disinfection of Lake Sturgeon eggs from the St. Lawrence River, New York","docAbstract":"Optimal fish husbandry to reduce the risk of disease is particularly important when using wild fish as the source for gametes. The propagation and reestablishment of Lake Sturgeon Acipenser fulvescens in New York waters to become a viable self-sustaining population is considered a high priority by managers. While standard hatchery egg disinfection practices have been used to prevent the transmission of diseases, data on the bacterial loads present on egg surfaces following iodine disinfection is lacking. Our study investigated the bacteria present on the outer surface of Lake Sturgeon eggs and the effectiveness of an iodine disinfection treatment in eliminating bacteria that could pose a threat to egg survival and cause hatchery disease outbreaks. During the springs of 2011–2013, 12 to 41 different species of bacteria were recovered from the outer egg surfaces prior to an iodine treatment; Aeromonas, Pseudomonas, Shewanella, and Chryseobacterium were the most common genera identified. Cohort eggs treated using the standard protocol of a single treatment of 50 mg/L iodine for 30 min resulted in an average of 57.8% reduction in bacterial CFU/g. While this is a significant reduction, bacteria were not completely eliminated and hatchery managers should be aware that pathogens could remain on Lake Sturgeon eggs following the standard iodine disinfection treatment.
","language":"English","publisher":"American Fisheries Society","publisherLocation":"Bethesda, MD","doi":"10.1080/15222055.2014.963768","usgsCitation":"Chalupnicki, M.A., Dittman, D.E., Starliper, C.E., and Iwanowicz, D.D., 2014, Efficacy of iodine for disinfection of Lake Sturgeon eggs from the St. Lawrence River, New York: North American Journal of Aquaculture, v. 77, no. 1, p. 82-89, https://doi.org/10.1080/15222055.2014.963768.","productDescription":"8 p.","startPage":"82","endPage":"89","numberOfPages":"8","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-057777","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":313075,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"New York","otherGeospatial":"St. Lawrence River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -74.66583251953125,\n 44.990055522906864\n ],\n [\n -74.68505859374999,\n 45.02403855956774\n ],\n [\n -74.78118896484375,\n 45.02209721486682\n ],\n [\n -74.94873046875,\n 45.00753503123719\n ],\n [\n -75.04898071289062,\n 44.95799590837475\n ],\n [\n -75.14236450195312,\n 44.91522187614324\n ],\n [\n -75.25634765625,\n 44.86949623772188\n ],\n [\n -75.37582397460938,\n 44.80522439622254\n ],\n [\n -75.49530029296875,\n 44.735027899515465\n ],\n [\n -75.706787109375,\n 44.58655513209543\n ],\n [\n -75.89218139648438,\n 44.44652641501047\n ],\n [\n -75.94985961914062,\n 44.37000528941461\n ],\n [\n -76.09954833984375,\n 44.34938634389529\n ],\n [\n -76.18881225585938,\n 44.3258129498022\n ],\n [\n -76.53350830078125,\n 44.213709909702054\n ],\n [\n -76.365966796875,\n 44.10040688311735\n ],\n [\n -76.2066650390625,\n 44.187127873177666\n ],\n [\n -75.992431640625,\n 44.26683800273895\n ],\n [\n -75.73974609375,\n 44.44652641501047\n ],\n [\n -75.7562255859375,\n 44.47789073724073\n ],\n [\n -75.69854736328124,\n 44.53959000445632\n ],\n [\n -75.48019409179686,\n 44.69404054463804\n ],\n [\n -75.27969360351562,\n 44.817889670988784\n ],\n [\n -75.10665893554688,\n 44.88603949514269\n ],\n [\n -74.92813110351562,\n 44.94633342311665\n ],\n [\n -74.80728149414062,\n 44.9715991458543\n ],\n [\n -74.66583251953125,\n 44.990055522906864\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"77","issue":"1","publishingServiceCenter":{"id":6,"text":"Columbus PSC"},"noUsgsAuthors":false,"publicationDate":"2014-12-16","publicationStatus":"PW","scienceBaseUri":"56850e8ae4b0a04ef49338d9","contributors":{"authors":[{"text":"Chalupnicki, Marc A. mchalupnicki@usgs.gov","contributorId":3236,"corporation":false,"usgs":true,"family":"Chalupnicki","given":"Marc","email":"mchalupnicki@usgs.gov","middleInitial":"A.","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":false,"id":583826,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Dittman, Dawn E. 0000-0002-0711-3732 ddittman@usgs.gov","orcid":"https://orcid.org/0000-0002-0711-3732","contributorId":2762,"corporation":false,"usgs":true,"family":"Dittman","given":"Dawn","email":"ddittman@usgs.gov","middleInitial":"E.","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":583827,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Starliper, Clifford E. cstarliper@usgs.gov","contributorId":1948,"corporation":false,"usgs":true,"family":"Starliper","given":"Clifford","email":"cstarliper@usgs.gov","middleInitial":"E.","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":583828,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Iwanowicz, Deborah D. 0000-0002-9613-8594 diwanowicz@usgs.gov","orcid":"https://orcid.org/0000-0002-9613-8594","contributorId":2253,"corporation":false,"usgs":true,"family":"Iwanowicz","given":"Deborah","email":"diwanowicz@usgs.gov","middleInitial":"D.","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":583829,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70118113,"text":"ds874 - 2014 - Groundwater-quality data in the Santa Cruz, San Gabriel, and Peninsular Ranges Hard Rock Aquifers study unit, 2011-2012: results from the California GAMA program","interactions":[],"lastModifiedDate":"2014-12-16T13:29:54","indexId":"ds874","displayToPublicDate":"2014-12-16T14:30:00","publicationYear":"2014","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":310,"text":"Data Series","code":"DS","onlineIssn":"2327-638X","printIssn":"2327-0271","active":false,"publicationSubtype":{"id":5}},"seriesNumber":"874","title":"Groundwater-quality data in the Santa Cruz, San Gabriel, and Peninsular Ranges Hard Rock Aquifers study unit, 2011-2012: results from the California GAMA program","docAbstract":"Groundwater quality in the 2,400-square-mile Santa Cruz, San Gabriel, and Peninsular Ranges Hard Rock Aquifers (Hard Rock) study unit was investigated by the U.S. Geological Survey (USGS) from March 2011 through March 2012, as part of the California State Water Resources Control Board (SWRCB) Groundwater Ambient Monitoring and Assessment (GAMA) Program’s Priority Basin Project (PBP). The GAMA-PBP was developed in response to the California Groundwater Quality Monitoring Act of 2001 and is being conducted in collaboration with the SWRCB and Lawrence Livermore National Laboratory (LLNL). The Hard Rock study unit was the 35th study unit to be sampled as part of the GAMA-PBP.
\n\n
The GAMA Hard Rock study was designed to provide a spatially unbiased assessment of untreated-groundwater quality in the primary aquifer system and to facilitate statistically consistent comparisons of untreated-groundwater quality throughout California. The primary aquifer system is defined as those parts of the aquifers corresponding to the perforation intervals of wells listed in the California Department of Public Health (CDPH) water-quality-monitoring database for the Hard Rock study unit. Groundwater quality in the primary aquifer system may differ from the quality in the shallower or deeper water-bearing zones; shallow groundwater may be more vulnerable to surficial contamination.
\n\n
In the Hard Rock study unit, groundwater samples were collected from 112 wells and springs in 3 study areas (the Santa Cruz, the San Gabriel, and the Peninsular Ranges) in San Mateo, Santa Clara, Santa Cruz, San Benito, Los Angeles, Orange, Riverside, San Bernardino, and San Diego Counties. Eighty-three wells and 11 springs were selected by using a spatially distributed, randomized grid-based method to provide statistical representation of the study unit (grid wells), and 15 wells and 3 springs were selected to aid in evaluation of water-quality issues (understanding wells).
\n\n
The groundwater samples were analyzed for field water-quality indicators; organic constituents; one constituent of special interest (perchlorate); naturally occurring inorganic constituents; and radioactive constituents. Naturally occurring isotopes and dissolved noble gases were also measured to help identify the sources and ages of the sampled groundwater. In total, 209 constituents and water-quality indicators were measured.
\n\n
Three types of quality-control samples (blanks, replicates, and matrix spikes) were collected at approximately 10 percent of the wells in the Hard Rock study unit, and the results for these samples were used to evaluate the quality of the data for the groundwater samples. Blanks rarely contained detectable concentrations of any constituent, suggesting that contamination from sample collection procedures was not a significant source of bias in the data for the groundwater samples. Replicate samples generally were within the limits of acceptable analytical reproducibility. Median matrix-spike recoveries were within the acceptable range (70 to 130 percent) for approximately 92 percent of the compounds.
\n\n
This study did not attempt to evaluate the quality of water delivered to consumers; after withdrawal from the ground, untreated groundwater typically is treated, disinfected, and (or) blended with other waters to maintain water quality. Regulatory benchmarks apply to water that is served to the consumer, not to untreated groundwater. However, to provide some context for the results, concentrations of constituents measured in the untreated groundwater were compared with regulatory and nonregulatory health-based benchmarks established by the U.S. Environmental Protection Agency (USEPA) and CDPH, and to nonregulatory benchmarks established for aesthetic concerns by the CDPH. Comparisons between data collected for this study and benchmarks for drinking water are for illustrative purposes only and are not indicative of compliance or non-compliance with those benchmarks.
\n\n
All organic constituents and most inorganic constituents that were detected in groundwater samples from the 112 wells in the Hard Rock study unit were detected at concentrations less than drinking-water benchmarks.
\n\n
Of the 149 organic and special-interest constituents, 34 were detected in groundwater samples; concentrations of all detected constituents were less than regulatory and nonregulatory health-based benchmarks. In total, VOCs were detected in 44 percent of the 94 grid wells sampled, pesticides and pesticide degradates were detected in 18 percent, and perchlorate was detected in 48 percent.
\n\n
Trace elements, nutrients, major and minor ions, and radioactive constituents were sampled for at 94 grid wells; most detected concentrations were less than health-based benchmarks. Exceptions in the Hard Rock study unit grid wells include 3 detections of arsenic greater than the USEPA maximum contaminant level (MCL-US) of 10 micrograms per liter (μg/L), 3 detections of boron greater than the CDPH notification level (NL-CA) of 1,000 μg/L, 2 detections of molybdenum greater than the USEPA lifetime health advisory level (HAL-US) of 40 μg/L, 2 detections of nitrite plus nitrate (as nitrogen) greater than the MCL-US of 10 milligrams per liter (mg/L), 3 detections of fluoride greater than the CDPH maximum contaminant level (MCL-CA) of 2 mg/L, 5 detections of radon-222 greater than the proposed MCL-US of 4,000 picocuries per liter (pCi/L), and 11 detections of unadjusted gross alpha radioactivity greater than the MCL-US of 15 pCi/L. Seven of the 11 samples having unadjusted gross alpha activity greater than the MCL-US also had total uranium concentrations greater than the MCL-US of 30 μg/L and (or) uranium activities greater than the MCL-CA of 20 pCi/L.
\n\n
Results for constituents with nonregulatory benchmarks set for aesthetic concerns showed that iron concentrations greater than the CDPH secondary maximum contaminant level (SMCL-CA) of 300 μg/L were detected in samples from 19 grid wells. Manganese concentrations greater than the SMCL-CA of 50 μg/L were detected in 27 grid wells. Chloride was detected at a concentration greater than the SMCL-CA upper benchmark of 500 mg/L in one grid well. TDS concentrations in three grid wells were greater than the SMCL-CA upper benchmark of 1,000 mg/L.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ds874","collaboration":"Prepared in cooperation with the California State Water Resources Control Board. A product of the California Groundwater Ambient Monitoring and Assessment (GAMA) Program.","usgsCitation":"Davis, T.A., and Shelton, J.L., 2014, Groundwater-quality data in the Santa Cruz, San Gabriel, and Peninsular Ranges Hard Rock Aquifers study unit, 2011-2012: results from the California GAMA program: U.S. Geological Survey Data Series 874, ix, 142 p., https://doi.org/10.3133/ds874.","productDescription":"ix, 142 p.","numberOfPages":"156","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-043444","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":296722,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ds874.jpg"},{"id":296720,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/ds/0874/"},{"id":296721,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/ds/0874/pdf/ds874.pdf","text":"Report","size":"7 MB","linkFileType":{"id":1,"text":"pdf"}}],"country":"United States","state":"California","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -124.45312499999999,\n 41.983994270935625\n ],\n [\n -119.81689453125,\n 41.96765920367816\n ],\n [\n -119.92675781249999,\n 38.993572058209466\n ],\n [\n -113.75244140624999,\n 34.415973384481866\n ],\n [\n -114.5654296875,\n 32.62087018318113\n ],\n [\n -118.0810546875,\n 32.52828936482526\n ],\n [\n -121.728515625,\n 35.191766965947394\n ],\n [\n -124.73876953125,\n 40.463666324587685\n ],\n [\n -124.45312499999999,\n 41.983994270935625\n ]\n ]\n ]\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"549157a7e4b0d0759afaad74","contributors":{"authors":[{"text":"Davis, Tracy A. 0000-0003-0253-6661 tadavis@usgs.gov","orcid":"https://orcid.org/0000-0003-0253-6661","contributorId":2715,"corporation":false,"usgs":true,"family":"Davis","given":"Tracy","email":"tadavis@usgs.gov","middleInitial":"A.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":false,"id":519137,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Shelton, Jennifer L. 0000-0001-8508-0270 jshelton@usgs.gov","orcid":"https://orcid.org/0000-0001-8508-0270","contributorId":1155,"corporation":false,"usgs":true,"family":"Shelton","given":"Jennifer","email":"jshelton@usgs.gov","middleInitial":"L.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":519135,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70135671,"text":"sim3312 - 2014 - Surficial geology and stratigraphy of Pleistocene Lake Manix, San Bernardino County, California","interactions":[],"lastModifiedDate":"2022-04-18T19:53:47.735487","indexId":"sim3312","displayToPublicDate":"2014-12-16T09:45:00","publicationYear":"2014","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":333,"text":"Scientific Investigations Map","code":"SIM","onlineIssn":"2329-132X","printIssn":"2329-1311","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"3312","title":"Surficial geology and stratigraphy of Pleistocene Lake Manix, San Bernardino County, California","docAbstract":"Pluvial Lake Manix and its surrounding drainage basin, in the central Mojave Desert of California, has been a focus of paleoclimate, surficial processes, and neotectonic studies by the U.S. Geological Survey (USGS) since about 2004. The USGS initiated studies of Lake Manix deposits to improve understanding of the paleoclimatic record and the shifts in atmospheric circulation that controlled precipitation in the Mojave Desert. Until approximately 25,000 years ago, Lake Manix was the terminus of the Mojave River, which drains northeasterly from the San Bernardino Mountains; the river currently terminates in the Soda Lake and Silver Lake playas. Pleistocene Lake Manix occupied several subbasins at its maximum extent. This map focuses on the extensive exposures created by incision of the Mojave River and its tributaries into the interbedded lacustrine and alluvial deposits within the central (Cady) and northeastern (Afton) subbasins of Lake Manix, and extends from the head of Afton Canyon to Manix Wash. The map illuminates the geomorphic development and depositional history of the lake and alluvial fans within the active tectonic setting of the eastern California shear zone, especially interactions with the left-lateral Manix fault. Lake Manix left an extraordinarily detailed but complex record of numerous transgressive-regressive sequences separated by desiccation and deposition of fan, eolian, and fluvial deposits, and punctuated by tectonic movements and a catastrophic flood that reconfigured the lake basin. Through careful observation of the intercalated lacustrine and fan sequences and by determining the precise elevations of unit contacts, this record was decoded to understand the response of the lake and river system to the interplay of climatic, geomorphic, and tectonic forces. These deposits are exposed in steep badland topography. Mapping was carried out mostly at scales of 1:12,000, although the map is presented at 1:24,000 scale, and employs custom unit nomenclature, with multiple subdivided lacustrine and alluvial fan units. In addition, many important units are very thin and cannot be mapped separately, or are covered by thin eolian sand, so these are commonly portrayed as stacks of units or combined units. These details are more accurately portrayed in the measured sections that accompany the map. Altitudes of many contacts were obtained using differentially corrected Global Positioning System (GPS) or, in some cases, lidar (light detection and ranging) data.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sim3312","usgsCitation":"Reheis, M.C., Redwine, J.R., Wan, E., McGeehin, J., and VanSistine, D., 2014, Surficial geology and stratigraphy of Pleistocene Lake Manix, San Bernardino County, California: U.S. Geological Survey Scientific Investigations Map 3312, Report: iv, 45 p.; 2 Sheets: 54 x 33 inches and 61 x 44 inches; Downloads Directory, https://doi.org/10.3133/sim3312.","productDescription":"Report: iv, 45 p.; 2 Sheets: 54 x 33 inches and 61 x 44 inches; Downloads Directory","numberOfPages":"53","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-036968","costCenters":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"links":[{"id":398996,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/usgs_thumb.jpg"},{"id":398995,"rank":6,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_101122.htm"},{"id":296697,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/sim/3312/pdf/SIM3312_sheet1.pdf","text":"Sheet 1","linkFileType":{"id":1,"text":"pdf"}},{"id":296689,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sim/3312/"},{"id":296699,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/sim/3312/downloads/"},{"id":296698,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/sim/3312/pdf/SIM3312_sheet2.pdf","text":"Sheet 2","linkFileType":{"id":1,"text":"pdf"}},{"id":296696,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sim/3312/pdf/sim3312.pdf","text":"Report","linkFileType":{"id":1,"text":"pdf"}}],"scale":"24000","country":"United States","state":"California","county":"San Bernardino County","otherGeospatial":"Lake Manix","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -116.5706,\n 34.9422\n ],\n [\n -116.3464,\n 34.9422\n ],\n [\n -116.3464,\n 35.0775\n ],\n [\n -116.5706,\n 35.0775\n ],\n [\n -116.5706,\n 34.9422\n ]\n ]\n ]\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"549157b3e4b0d0759afaad76","contributors":{"authors":[{"text":"Reheis, Marith C. 0000-0002-8359-323X mreheis@usgs.gov","orcid":"https://orcid.org/0000-0002-8359-323X","contributorId":1196,"corporation":false,"usgs":true,"family":"Reheis","given":"Marith","email":"mreheis@usgs.gov","middleInitial":"C.","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":false,"id":536725,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Redwine, Joanna R.","contributorId":130966,"corporation":false,"usgs":false,"family":"Redwine","given":"Joanna","email":"","middleInitial":"R.","affiliations":[{"id":7183,"text":"U.S. Bureau of Reclamation","active":true,"usgs":false}],"preferred":false,"id":536726,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Wan, Elmira 0000-0002-9255-112X ewan@usgs.gov","orcid":"https://orcid.org/0000-0002-9255-112X","contributorId":3434,"corporation":false,"usgs":true,"family":"Wan","given":"Elmira","email":"ewan@usgs.gov","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":536724,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"McGeehin, John P. 0000-0002-5320-6091 mcgeehin@usgs.gov","orcid":"https://orcid.org/0000-0002-5320-6091","contributorId":3444,"corporation":false,"usgs":true,"family":"McGeehin","given":"John P.","email":"mcgeehin@usgs.gov","affiliations":[{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true}],"preferred":true,"id":536727,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"VanSistine, D. Paco 0000-0003-1166-2547","orcid":"https://orcid.org/0000-0003-1166-2547","contributorId":61906,"corporation":false,"usgs":true,"family":"VanSistine","given":"D. Paco","affiliations":[],"preferred":false,"id":536723,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70135642,"text":"sir20145213 - 2014 - Steady-state numerical groundwater flow model of the Great Basin carbonate and alluvial aquifer system","interactions":[],"lastModifiedDate":"2021-12-15T20:21:17.888329","indexId":"sir20145213","displayToPublicDate":"2014-12-15T14:45:00","publicationYear":"2014","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2014-5213","title":"Steady-state numerical groundwater flow model of the Great Basin carbonate and alluvial aquifer system","docAbstract":"This report describes the construction, calibration, evaluation, and results of a steady-state numerical groundwater flow model of the Great Basin carbonate and alluvial aquifer system that was developed as part of the U.S. Geological Survey National Water Census Initiative to evaluate the nation’s groundwater availability. The study area spans 110,000 square miles across five states. The numerical model uses MODFLOW-2005, and incorporates and tests complex hydrogeologic and hydrologic elements of a conceptual understanding of an interconnected groundwater system throughout the region, including mountains, basins, consolidated rocks, and basin fill. The level of discretization in this model has not been previously available throughout the study area.
\nObservations used to calibrate the model are those of water levels and discharge to evapotranspiration, springs, rivers, and lakes. Composite scaled sensitivities indicate the simulated values of discharge to springs, rivers, and lakes provide as much information about model parameters as do simulated water-level values. The model has 176 parameters and little parameter correlation. The simulated equivalents to observations provide enough information to constrain most parameters to smaller ranges than the conceptual constraints, and most parameter values are within reasonable ranges.
\nModel fit to observations, comparison of simulated to conceptual water-level contours, and comparison of simulated to conceptual water budgets indicate this model provides a reasonable representation of the regional groundwater system. Eighty-six percent of the simulated values of water levels in wells are within 119 feet (one standard deviation of the error) of the observed values. Ninety percent of the simulated discharges are within 30 percent of the observed values. Total simulated recharge in the study area is within 10 percent of the conceptual amount; total simulated discharge is the same as conceptual discharge. Comparison of simulated hydraulic heads with the conceptual potentiometric surface indicates that the model accurately depicts major features of the hydraulic-head distribution. The incorporation of new recharge estimates and of mountain springs and streams as model observations creates higher simulated recharge mounds under many mountain ranges and highlights that in many cases, the regional flow paths go around, not through (or under) mountain ranges. Results from the model show that much of the flow in the groundwater system occurs in deeper layers, even though about 86 percent of the discharge occurs in layer 1. Over 95 percent of the recharge moves down from layer 1, and about 25 percent moves down to layer 8.
\nThe model was used to delineate six simulated groundwater flow regions that connect recharge areas to discharge areas. The eastern Great Salt Lake and Great Salt Lake Desert model regions contain 75 percent of the groundwater budget, but only 42 percent of the study area. In contrast, the more southern Death Valley and Colorado model regions contain only 12 percent of the groundwater budget, but 37 percent of the study area.
\nExamples of potential use of the model to investigate the groundwater system include (1) the effects of different recharge, (2) different interpretations of the extent or offset of long faults or fault zones, and (3) different conceptual models of the spatial variation of hydraulic properties. The model can also be used to examine the ultimate effects of groundwater withdrawals on a regional scale, to provide boundary conditions for local-scale models, and to guide data collection.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20145213","usgsCitation":"Brooks, L.E., Masbruch, M.D., Sweetkind, D.S., and Buto, S.G., 2014, Steady-state numerical groundwater flow model of the Great Basin carbonate and alluvial aquifer system: U.S. Geological Survey Scientific Investigations Report 2014-5213, Report: x, 124 p.; 2 Plates: 16.5 x 22.0 inches; Appendix Tables; Model Files, https://doi.org/10.3133/sir20145213.","productDescription":"Report: x, 124 p.; 2 Plates: 16.5 x 22.0 inches; Appendix Tables; Model Files","numberOfPages":"138","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-037343","costCenters":[{"id":465,"text":"Nevada Water Science Center","active":true,"usgs":true},{"id":610,"text":"Utah Water Science Center","active":true,"usgs":true}],"links":[{"id":296686,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir20145213.jpg"},{"id":296683,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/sir/2014/5213/downloads/sir2014-5213_plates1and2.zip","text":"Plates 1 and 2","size":"11.6 MB","description":"Plates 1 and 2"},{"id":296681,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2014/5213/"},{"id":296685,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/sir/2014/5213/downloads/sir2014-5213_modelfiles.zip","text":"Model Files","size":"143.3 MB","description":"Model Files"},{"id":296684,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2014/5213/downloads/sir2014-5213_appendixexceltables.zip","text":"Appendix Tables","size":"535 kB","description":"Appendix Tables"},{"id":296682,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2014/5213/pdf/sir2014-5213.pdf","size":"32.3 MB","linkFileType":{"id":1,"text":"pdf"},"description":"Report"}],"projection":"Albers Equal Area Conic Projection","datum":"North American Datum 1983","country":"United States","otherGeospatial":"Great Basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -118.5205078125,\n 35.460669951495305\n ],\n [\n -118.5205078125,\n 42.52069952914966\n ],\n [\n -111.0498046875,\n 42.52069952914966\n ],\n [\n -111.0498046875,\n 35.460669951495305\n ],\n [\n -118.5205078125,\n 35.460669951495305\n ]\n ]\n ]\n }\n }\n ]\n}","publicComments":"Groundwater Resources Program","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"54900630e4b020a14785d24a","contributors":{"authors":[{"text":"Brooks, Lynette E. 0000-0002-9074-0939 lebrooks@usgs.gov","orcid":"https://orcid.org/0000-0002-9074-0939","contributorId":2718,"corporation":false,"usgs":true,"family":"Brooks","given":"Lynette","email":"lebrooks@usgs.gov","middleInitial":"E.","affiliations":[{"id":610,"text":"Utah Water Science Center","active":true,"usgs":true}],"preferred":true,"id":536694,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Masbruch, Melissa D. 0000-0001-6568-160X mmasbruch@usgs.gov","orcid":"https://orcid.org/0000-0001-6568-160X","contributorId":1902,"corporation":false,"usgs":true,"family":"Masbruch","given":"Melissa","email":"mmasbruch@usgs.gov","middleInitial":"D.","affiliations":[{"id":610,"text":"Utah Water Science Center","active":true,"usgs":true}],"preferred":true,"id":536695,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Sweetkind, Donald S. dsweetkind@usgs.gov","contributorId":127801,"corporation":false,"usgs":true,"family":"Sweetkind","given":"Donald","email":"dsweetkind@usgs.gov","middleInitial":"S.","affiliations":[],"preferred":false,"id":536697,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Buto, Susan G. 0000-0002-1107-9549 sbuto@usgs.gov","orcid":"https://orcid.org/0000-0002-1107-9549","contributorId":1057,"corporation":false,"usgs":true,"family":"Buto","given":"Susan","email":"sbuto@usgs.gov","middleInitial":"G.","affiliations":[{"id":465,"text":"Nevada Water Science Center","active":true,"usgs":true},{"id":610,"text":"Utah Water Science Center","active":true,"usgs":true}],"preferred":true,"id":536696,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70148179,"text":"70148179 - 2014 - Tree growth and recruitment in a leveed floodplain forest in the Mississippi River Alluvial Valley, USA","interactions":[],"lastModifiedDate":"2015-05-26T10:56:43","indexId":"70148179","displayToPublicDate":"2014-12-15T12:00:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1687,"text":"Forest Ecology and Management","active":true,"publicationSubtype":{"id":10}},"title":"Tree growth and recruitment in a leveed floodplain forest in the Mississippi River Alluvial Valley, USA","docAbstract":"Flooding is a defining disturbance in floodplain forests affecting seed germination, seedling establishment, and tree growth. Globally, flood control, including artificial levees, dams, and channelization has altered flood regimes in floodplains. However, a paucity of data are available in regards to the long-term effects of levees on stand establishment and tree growth in floodplain forests. In this study, we used dendrochronological techniques to reconstruct tree recruitment and tree growth over a 90-year period at three stands within a ring levee in the Mississippi River Alluvial Valley (MAV) and to evaluate whether recruitment patterns and tree growth changed following levee construction. We hypothesized that: (1) sugarberry is increasing in dominance and overcup oak (Quercus lyrata) is becoming less dominant since the levee, and that changes in hydrology are playing a greater role than canopy disturbance in these changes in species dominance; and (2) that overcup oak growth has declined following construction of the levee and cessation of overbank flooding whereas that of sugarberry has increased. Recruitment patterns shifted from flood-tolerant overcup oak to flood-intolerant sugarberry (Celtis laevigata) after levee construction. None of the 122 sugarberry trees cored in this study established prior to the levee, but it was the most common species established after the levee. The mechanisms behind the compositional change are unknown, however, the cosmopolitan distribution of overcup oak during the pre-levee period and sugarberry during the post-levee period, the lack of sugarberry establishment in the pre-levee period, and the confinement of overcup oak regeneration to the lowest areas in each stand after harvest in the post-levee period indicate that species-specific responses to flooding and light availability are forcing recruitment patterns. Overcup oak growth was also affected by levee construction, but in contrast to our hypothesis, growth actually increased for several decades before declining during a drought in the late 1990s. We interpret this result as removal of flood stress following levee construction. This finding emphasizes the fact that flooding can be stressful to trees regardless of their flood tolerance and that growth in floodplain trees can be sustained provided adequate soil moisture is present, regardless of the source of soil moisture. However, future research efforts should focus on the long-term effect of hydrologic modification on stand development and on how hydrologic modifications, such as elimination of surface flooding and groundwater declines, affect the vulnerability of floodplain forests to drought.
","language":"English","publisher":"Elsevier Science","publisherLocation":"Amsterdam","doi":"10.1016/j.foreco.2014.08.024","collaboration":"Arkansas Game and Fish-Commission; Louisiana Department of Wildlife and Fisheries, U.S. Fish and Wildlife Service; U.S. Geological Survey Louisiana Fish and Wildlife Cooperative Research Unit","usgsCitation":"Gee, H.K., King, S.L., and Keim, R., 2014, Tree growth and recruitment in a leveed floodplain forest in the Mississippi River Alluvial Valley, USA: Forest Ecology and Management, v. 334, p. 85-95, https://doi.org/10.1016/j.foreco.2014.08.024.","productDescription":"11 p.","startPage":"85","endPage":"95","numberOfPages":"11","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-055252","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":300781,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"334","publishingServiceCenter":{"id":8,"text":"Raleigh PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"55659958e4b0d9246a9eb647","contributors":{"authors":[{"text":"Gee, Hugo K.W.","contributorId":140925,"corporation":false,"usgs":false,"family":"Gee","given":"Hugo","email":"","middleInitial":"K.W.","affiliations":[],"preferred":false,"id":547604,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"King, Sammy L. 0000-0002-5364-6361 sking@usgs.gov","orcid":"https://orcid.org/0000-0002-5364-6361","contributorId":557,"corporation":false,"usgs":true,"family":"King","given":"Sammy","email":"sking@usgs.gov","middleInitial":"L.","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":547537,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Keim, Richard F.","contributorId":21858,"corporation":false,"usgs":true,"family":"Keim","given":"Richard F.","affiliations":[],"preferred":false,"id":547605,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70135422,"text":"70135422 - 2014 - Nitrogen speciation and trends, and prediction of denitrification extent, in shallow US groundwater","interactions":[],"lastModifiedDate":"2014-12-15T10:46:55","indexId":"70135422","displayToPublicDate":"2014-12-15T11:45:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2342,"text":"Journal of Hydrology","active":true,"publicationSubtype":{"id":10}},"title":"Nitrogen speciation and trends, and prediction of denitrification extent, in shallow US groundwater","docAbstract":"Uncertainties surrounding nitrogen cycling complicate assessments of the environmental effects of nitrogen use and our understanding of the global carbon–nitrogen cycle. In this paper, we synthesize data from 877 ambient-monitoring wells across the US to frame broad patterns of nitrogen speciation and trends. At these sites, groundwater frequently contains substantial co-occurring NO3− and XSN2 (N2 from denitrification), reflecting active/ongoing denitrification and/or a mixture of undenitrified and denitrified groundwater. NO3− and NH4+ essentially do not co-occur, indicating that the dominant source of NH4+ at these sites likely is not dissimilatory reduction of NO3− to NH4+. Positive correlations of NH4+ with apparent age, CH4, dissolved organic carbon, and indicators of reduced conditions are consistent with NH4+ mobilization from degradation of aquifer organic matter and contraindicate an anthropogenic source of NH4+ for most sites. Glacial aquifers and eastern sand and gravel aquifers generally have lower proportions of NO3− and greater proportions of XSN2 than do fractured rock and karst aquifers and western sand and gravel aquifers. NO3− dominates in the youngest groundwater, but XSN2 increases as residence time increases. Temporal patterns of nitrogen speciation and concentration reflect (1) changing NO3− loads over time, (2) groundwater residence-time controls on NH4+ mobilization from solid phases, and (3) groundwater residence-time controls on denitrification. A simple classification tree using readily available variables (a national coverage of soil water depth, generalized geology) or variables reasonably estimated in many aquifers (residence time) identifies categorical denitrification extent (<10%, 10–50%, and >50%) with 79% accuracy in an independent testing set, demonstrating a predictive application based on the interconnected effects of redox, geology, and residence time.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.jhydrol.2013.11.048","usgsCitation":"Hinkle, S.R., and Tesoriero, A., 2014, Nitrogen speciation and trends, and prediction of denitrification extent, in shallow US groundwater: Journal of Hydrology, v. 509, p. 343-353, https://doi.org/10.1016/j.jhydrol.2013.11.048.","productDescription":"11 p.","startPage":"343","endPage":"353","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-028945","costCenters":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"links":[{"id":296675,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","volume":"509","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5490062de4b020a14785d246","contributors":{"authors":[{"text":"Hinkle, Stephen R. srhinkle@usgs.gov","contributorId":1171,"corporation":false,"usgs":true,"family":"Hinkle","given":"Stephen","email":"srhinkle@usgs.gov","middleInitial":"R.","affiliations":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"preferred":true,"id":527120,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Tesoriero, Anthony J.","contributorId":40207,"corporation":false,"usgs":true,"family":"Tesoriero","given":"Anthony J.","affiliations":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"preferred":false,"id":536673,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70135346,"text":"sim3309 - 2014 - Bedrock geologic and structural map through the western Candor Colles region of Mars","interactions":[],"lastModifiedDate":"2023-03-20T18:07:11.900565","indexId":"sim3309","displayToPublicDate":"2014-12-12T12:30:00","publicationYear":"2014","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":333,"text":"Scientific Investigations Map","code":"SIM","onlineIssn":"2329-132X","printIssn":"2329-1311","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"3309","title":"Bedrock geologic and structural map through the western Candor Colles region of Mars","docAbstract":"The Candor Colles are a population of low, conical hills along the southeast flank of Ceti Mensa, in west Candor Chasma, within the Valles Marineris system of Mars (fig. 1). Ceti Mensa and the adjacent Candor Mensa are mounds of layered sedimentary deposits and are the most prominent landforms within west Candor Chasma. Prior to the arrival of the Mars Reconnaissance Orbiter (MRO) in orbit around Mars in 2006 (Zurek and Smrekar, 2007), geologic maps of the area utilized the relatively low resolution Viking Orbiter photomosaics (20–150 m/pixel). Geologic maps covering west Candor Chasma were created at scales of 1:15,000,000 for the western equatorial region of Mars (Scott and Tanaka, 1986), 1:2,000,000 for the Valles Marineris region (Witbeck and others, 1991), and 1:500,000 for the far eastern part of west Candor Chasma (Mars Transverse Mercator quadrangle–05072; Lucchitta, 1999).
\n\n
Previous structural mapping in west Candor Chasma at scales of less than 1:24,000 (Okubo and others, 2008; Okubo, 2010) employed digital terrain models (DTMs), with 1-m post spacings, derived from stereo MRO High Resolution Imaging Science Experiment (HiRISE) imagery (McEwen and others, 2010) and focused on examining the relative timing between deposition of the youngest unit of the layered deposits in this area (unit Avme of Witbeck and others, 1991) relative to regional faulting related to chasma formation. These previous mapping efforts on the southwest flank of Ceti Mensa demonstrated that unit Avme is not deformed by faults attributed to formation of the chasma. Studies of other layered deposits (primarily unit Hvl, but also including units Avme, Avsl, Avsd, and Avfs; Witbeck and others, 1991) exposed along the southeast flank of Ceti Mensa using a High-Resolution Stereo Camera (HRSC) digital terrain model (DTM) (50 m/pixel) refined the local stratigraphy and revealed evidence for syntectonic deposition of these deposits (Fueten and others, 2006, 2008; Jaumann and others, 2007; Birnie and others, 2012).
\n\n
Layered deposits such as those that constitute Ceti Mensa are widespread throughout the interior regions of Valles Marineris (Witbeck and others, 1991). These sedimentary deposits have been variously interpreted as eolian sediments (Nedell and others, 1987), hyaloclastic debris (Chapman and Tanaka, 2001; Komatsu and others, 2004), lacustrine or fluvial sediment (Dromart and others, 2007; Mangold and others, 2008; Metz and others, 2009), pyroclastic deposits (Hynek and others, 2003), evaporites (Mangold and others, 2008; Andrews-Hanna and others, 2010), or various combinations thereof.
\n\n
Recent analysis of data from the MRO Compact Reconnaissance Imaging Spectrometer for Mars (CRISM) shows that these sediments consist primarily of hydrated sulfates (Murchie and others, 2009a,b). Further, hydrologic modeling indicates that spring-fed lakes likely occurred within the chasma (Andrews-Hanna and others, 2010). These recent findings point to a scenario in which the layered deposits accumulated as sequences of evaporites precipitating in hypersaline lakes, with contemporaneous trapping of eolian dust and sand, diagenesis, and iron-cycling, interspersed with periods of eolian and fluvial erosion (Murchie and others, 2009a). Water vapor released from these lakes may have also driven localized precipitation of snow and accumulation of layered deposits on the adjacent plateaus (Kite and others, 2011a,b). This scenario is in contrast to recent alternative interpretations that the layered deposits formed within the chasma through weathering of dust-rich ice deposits (Niles and Michalski, 2009; Michalski and Niles, 2012).
\n
The structure and geology of the layered deposits in the Candor Colles region corresponding to units Avfs, Avme, and Hvl of Witbeck and others (1991) are reevaluated in this 1:18,000-scale map. The objectives herein are to gather high-resolution structural measurements to (1) refine the previous unit boundaries in this area established by Witbeck and others (1991), (2) revise the local stratigraphy where necessary, (3) characterize bed forms to help constrain depositional processes, and (4) determine the styles and extent of deformation to better inform reconstructions of the local post-depositional geologic history.
Water, bed sediment, and biota were sampled in streams from Butte to near Missoula, Montana, as part of a monitoring program in the upper Clark Fork Basin of western Montana. The sampling program was led by the U.S. Geological Survey in cooperation with the U.S. Environmental Protection Agency to characterize aquatic resources in the Clark Fork Basin, with emphasis on trace elements associated with historic mining and smelting activities. Sampling sites were located on the Clark Fork and selected tributaries. Water samples were collected periodically at 20 sites from October 2012 through September 2013. Bed-sediment and biota samples were collected once at 13 sites during August 2013.
\n\n
This report presents the analytical results and quality-assurance data for water-quality, bed-sediment, and biota samples collected at sites from October 2012 through September 2013. Water-quality data include concentrations of selected major ions, trace elements, and suspended sediment. Turbidity and dissolved organic carbon were analyzed for water samples collected at the four sites where seasonal daily values of turbidity were being determined. Daily values of mean suspended-sediment concentration and suspended-sediment discharge were determined for four sites. Bed-sediment data include trace-element concentrations in the fine-grained fraction. Biological data include trace-element concentrations in whole-body tissue of aquatic benthic insects. Statistical sum-maries of water-quality, bed-sediment, and biological data for sites in the upper Clark Fork Basin are provided for the period of record.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20141244","collaboration":"Prepared in cooperation with the U.S. Environmental Protection Agency","usgsCitation":"Dodge, K.A., Hornberger, M.I., and Dyke, J., 2014, Water-quality, bed-sediment, and biological data (October 2012 through September 2013) and statistical summaries of data for streams in the Clark Fork Basin, Montana: U.S. Geological Survey Open-File Report 2014-1244, vi, 133 p., https://doi.org/10.3133/ofr20141244.","productDescription":"vi, 133 p.","numberOfPages":"144","onlineOnly":"N","additionalOnlineFiles":"N","temporalStart":"2012-10-01","temporalEnd":"2013-09-30","ipdsId":"IP-059451","costCenters":[{"id":685,"text":"Wyoming-Montana Water Science Center","active":false,"usgs":true}],"links":[{"id":296629,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2014/1244/pdf/ofr2014-1244.pdf","size":"3.2 MB","linkFileType":{"id":1,"text":"pdf"},"description":"Report"},{"id":296627,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2014/1244/"},{"id":296630,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr20141244.jpg"}],"datum":"North American Datum of 1927","country":"United States","state":"Montana","otherGeospatial":"Clark Fork Basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -114.3017578125,\n 45.775186183521036\n ],\n [\n -114.3017578125,\n 47.025206001585396\n ],\n [\n -112.28576660156249,\n 47.025206001585396\n ],\n [\n -112.28576660156249,\n 45.775186183521036\n ],\n [\n -114.3017578125,\n 45.775186183521036\n ]\n ]\n ]\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"548c11b7e4b0ca8c43c3694f","contributors":{"authors":[{"text":"Dodge, Kent A. kdodge@usgs.gov","contributorId":1036,"corporation":false,"usgs":true,"family":"Dodge","given":"Kent","email":"kdodge@usgs.gov","middleInitial":"A.","affiliations":[{"id":5050,"text":"WY-MT Water Science Center","active":true,"usgs":true}],"preferred":true,"id":527014,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hornberger, Michelle I. 0000-0002-7787-3446 mhornber@usgs.gov","orcid":"https://orcid.org/0000-0002-7787-3446","contributorId":1037,"corporation":false,"usgs":true,"family":"Hornberger","given":"Michelle","email":"mhornber@usgs.gov","middleInitial":"I.","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":527015,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Dyke, Jessica jldyke@usgs.gov","contributorId":1035,"corporation":false,"usgs":true,"family":"Dyke","given":"Jessica","email":"jldyke@usgs.gov","affiliations":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"preferred":false,"id":527016,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70201454,"text":"70201454 - 2014 - Proper handling of animal tissues from the field to the laboratory supports reliable biomarker endpoints","interactions":[],"lastModifiedDate":"2018-12-13T12:22:31","indexId":"70201454","displayToPublicDate":"2014-12-11T11:45:48","publicationYear":"2014","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"title":"Proper handling of animal tissues from the field to the laboratory supports reliable biomarker endpoints","docAbstract":"In the endeavor to assess potential effects to the Gulf of Mexico ecosystem from the Mississippi Canyon 252 incident, referred to as the Deepwater Horizon oil spill, various environmental data have been collected. Whereas initial efforts have included satellite tracking and sediment and water sampling to estimate the geographical scope of oiling, research on biological samples can provide insights into potential physiological responses to oil if it was present in the food web, sediment, or water column. Fish species are ideal model organisms for studying responses to water- and sediment-borne contaminants due to their life history (Jenkins et al. 2014), and several Gulf of Mexico fish species were studied by scientists after this incident. Typical field data collected on fish reflect organism condition and include observations such as fish length, weight, gonad condition, condition factor (weight in relation to length), parasite load, and color of organs (Schmitt and Dethloff 2000). However, if physiological responses occurred due to oil exposure, effects would not be immediately visible using organism-level observations alone. Changes occur first at the organ, tissue, cell, or molecular levels, and these responses can be measured by using biomarker assays (van der Oost et al. 2003).
","largerWorkTitle":"Impacts of oil spill disasters on marine habitats and fisheries in North America","language":"English","publisher":"CRC Press","isbn":"9781466557208 ","usgsCitation":"Olivier, H.M., and Jenkins, J.A., 2014, Proper handling of animal tissues from the field to the laboratory supports reliable biomarker endpoints, chap. of Impacts of oil spill disasters on marine habitats and fisheries in North America, p. 81-93.","productDescription":"13 p.","startPage":"81","endPage":"93","ipdsId":"IP-046164","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":360242,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":360241,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://www.crcpress.com/Impacts-of-Oil-Spill-Disasters-on-Marine-Habitats-and-Fisheries-in-North/Alford-Peterson-Green/p/book/9781466557208"}],"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5c137dd5e4b006c4f85148a0","contributors":{"editors":[{"text":"Alford, J. B.","contributorId":120313,"corporation":false,"usgs":true,"family":"Alford","given":"J.","email":"","middleInitial":"B.","affiliations":[],"preferred":false,"id":754140,"contributorType":{"id":2,"text":"Editors"},"rank":1},{"text":"Peterson, Mark S.","contributorId":8979,"corporation":false,"usgs":true,"family":"Peterson","given":"Mark","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":754141,"contributorType":{"id":2,"text":"Editors"},"rank":2},{"text":"Green, Christopher C.","contributorId":111389,"corporation":false,"usgs":true,"family":"Green","given":"Christopher","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":754142,"contributorType":{"id":2,"text":"Editors"},"rank":3}],"authors":[{"text":"Olivier, Heather M.","contributorId":23245,"corporation":false,"usgs":true,"family":"Olivier","given":"Heather","email":"","middleInitial":"M.","affiliations":[{"id":455,"text":"National Wetlands Research Center","active":true,"usgs":true}],"preferred":false,"id":754139,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Jenkins, Jill A. 0000-0002-5087-0894 jenkinsj@usgs.gov","orcid":"https://orcid.org/0000-0002-5087-0894","contributorId":2710,"corporation":false,"usgs":true,"family":"Jenkins","given":"Jill","email":"jenkinsj@usgs.gov","middleInitial":"A.","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true},{"id":455,"text":"National Wetlands Research Center","active":true,"usgs":true}],"preferred":true,"id":754138,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70133603,"text":"ds900 - 2014 - Geospatial compilation of historical water-level changes in the Chicot and Evangeline aquifers 1977-2013 and Jasper aquifer 2000-13, Gulf Coast aquifer system, Houston-Galveston region, Texas","interactions":[],"lastModifiedDate":"2017-03-29T16:52:12","indexId":"ds900","displayToPublicDate":"2014-12-11T11:30:00","publicationYear":"2014","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":310,"text":"Data Series","code":"DS","onlineIssn":"2327-638X","printIssn":"2327-0271","active":false,"publicationSubtype":{"id":5}},"seriesNumber":"900","title":"Geospatial compilation of historical water-level changes in the Chicot and Evangeline aquifers 1977-2013 and Jasper aquifer 2000-13, Gulf Coast aquifer system, Houston-Galveston region, Texas","docAbstract":"The U.S. Geological Survey (USGS) in cooperation with the Harris-Galveston Subsidence District, City of Houston, Fort Bend Subsidence District, Lone Star Groundwater Conservation District, and Brazoria County Groundwater Conservation District has produced an annual series of reports that depict water-level changes in the Chicot, Evangeline, and Jasper aquifers of the Gulf Coast aquifer system in the Houston-Galveston region, Texas, from 1977 to 2013. Changes are determined from water-level measurements between December and March of each year from groundwater wells screened in one of the three aquifers. Existing published maps and unpublished geographic information system (GIS) datasets were compiled into a comprehensive geodatabase of all water-level-change maps produced as part of this multiagency effort. Annual water-level-change maps were georeferenced and digitized where existing GIS data were unavailable (1979–99). Existing GIS data available for 2000–13 were included in the geodatabase. The compilation contains 121 datasets showing water-level changes for each primary aquifer of the Gulf Coast aquifer system: 56 for the Chicot aquifer (1977; 1979–2013 and 1990; 1993–2013), 56 for the Evangeline aquifer (1977; 1979–2013 and 1990; 1993–2013), and 9 for the Jasper aquifer (2000; 2005–13).
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ds900","collaboration":"Prepared in cooperation with the Harris-Galveston Subsidence District, City of Houston, Fort Bend Subsidence District, Lone Star Groundwater Conservation District, and Brazoria County Groundwater Conservation District","usgsCitation":"Johnson, M., and Linard, J.I., 2014, Geospatial compilation of historical water-level changes in the Chicot and Evangeline aquifers 1977-2013 and Jasper aquifer 2000-13, Gulf Coast aquifer system, Houston-Galveston region, Texas: U.S. Geological Survey Data Series 900, HTML Document; Downloads Directory, https://doi.org/10.3133/ds900.","productDescription":"HTML Document; Downloads Directory","onlineOnly":"Y","additionalOnlineFiles":"Y","temporalStart":"1977-01-01","temporalEnd":"2013-12-31","ipdsId":"IP-058449","costCenters":[{"id":583,"text":"Texas Water Science Center","active":true,"usgs":true}],"links":[{"id":296620,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ds900.PNG"},{"id":296132,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/ds/0900/"},{"id":296619,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/ds/0900/downloads/","text":"Downloads Directory","description":"Downloads Directory"}],"projection":"Universal Transverse Mercator projection, zone 15","datum":"North American Datum of 1927","country":"United States","state":"Texas","city":"Galveston, Houston","otherGeospatial":"Houston-Galveston region","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -94.3505859375,\n 29.554345125748267\n ],\n [\n -94.52636718749999,\n 30.031055426540206\n ],\n [\n -94.7021484375,\n 30.29701788337205\n ],\n [\n -94.976806640625,\n 30.675715404167743\n ],\n [\n -95.07568359375,\n 30.829139422013956\n ],\n [\n -95.25970458984374,\n 30.954057859276126\n ],\n [\n -95.614013671875,\n 30.95876857077987\n ],\n [\n -96.064453125,\n 30.798474179567823\n ],\n [\n -96.2841796875,\n 30.64027517241868\n ],\n [\n -96.3446044921875,\n 30.462879341709886\n ],\n [\n -96.2237548828125,\n 30.073847754270204\n ],\n [\n -96.03149414062499,\n 29.410890376109\n ],\n [\n -95.82275390625,\n 29.080175989623203\n ],\n [\n -95.6304931640625,\n 28.9072060763367\n ],\n [\n -95.3558349609375,\n 28.8831596093235\n ],\n [\n -94.7515869140625,\n 29.291189838184863\n ],\n [\n -94.3505859375,\n 29.554345125748267\n ]\n ]\n ]\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"548ac02de4b00f366bee37a6","contributors":{"authors":[{"text":"Johnson, Michaela R. 0000-0001-6133-0247 mrjohns@usgs.gov","orcid":"https://orcid.org/0000-0001-6133-0247","contributorId":1013,"corporation":false,"usgs":true,"family":"Johnson","given":"Michaela R.","email":"mrjohns@usgs.gov","affiliations":[{"id":583,"text":"Texas Water Science Center","active":true,"usgs":true},{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true},{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":525296,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Linard, Joshua I. jilinard@usgs.gov","contributorId":1465,"corporation":false,"usgs":true,"family":"Linard","given":"Joshua","email":"jilinard@usgs.gov","middleInitial":"I.","affiliations":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"preferred":true,"id":525297,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70135103,"text":"ds892 - 2014 - DOI/GTN-P climate and active-layer data acquired in the National Petroleum Reserve-Alaska and the Arctic National Wildlife Refuge","interactions":[{"subject":{"id":70073510,"text":"ds812 - 2014 - DOI/GTN-P climate and active-layer data acquired in the National Petroleum Reserve: Alaska and the Arctic National Wildlife Refuge, 1998-2011","indexId":"ds812","publicationYear":"2014","noYear":false,"title":"DOI/GTN-P climate and active-layer data acquired in the National Petroleum Reserve: Alaska and the Arctic National Wildlife Refuge, 1998-2011"},"predicate":"SUPERSEDED_BY","object":{"id":70135103,"text":"ds892 - 2014 - DOI/GTN-P climate and active-layer data acquired in the National Petroleum Reserve-Alaska and the Arctic National Wildlife Refuge","indexId":"ds892","publicationYear":"2014","noYear":false,"title":"DOI/GTN-P climate and active-layer data acquired in the National Petroleum Reserve-Alaska and the Arctic National Wildlife Refuge"},"id":1},{"subject":{"id":70135103,"text":"ds892 - 2014 - DOI/GTN-P climate and active-layer data acquired in the National Petroleum Reserve-Alaska and the Arctic National Wildlife Refuge","indexId":"ds892","publicationYear":"2014","noYear":false,"title":"DOI/GTN-P climate and active-layer data acquired in the National Petroleum Reserve-Alaska and the Arctic National Wildlife Refuge"},"predicate":"SUPERSEDED_BY","object":{"id":70168397,"text":"ds977 - 2016 - DOI/GTN-P Climate and active-layer data acquired in the National Petroleum Reserve–Alaska and the Arctic National Wildlife Refuge, 1998–2014","indexId":"ds977","publicationYear":"2016","noYear":false,"title":"DOI/GTN-P Climate and active-layer data acquired in the National Petroleum Reserve–Alaska and the Arctic National Wildlife Refuge, 1998–2014"},"id":2}],"supersededBy":{"id":70168397,"text":"ds977 - 2016 - DOI/GTN-P Climate and active-layer data acquired in the National Petroleum Reserve–Alaska and the Arctic National Wildlife Refuge, 1998–2014","indexId":"ds977","publicationYear":"2016","noYear":false,"title":"DOI/GTN-P Climate and active-layer data acquired in the National Petroleum Reserve–Alaska and the Arctic National Wildlife Refuge, 1998–2014"},"lastModifiedDate":"2016-06-23T15:13:40","indexId":"ds892","displayToPublicDate":"2014-12-11T11:30:00","publicationYear":"2014","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":310,"text":"Data Series","code":"DS","onlineIssn":"2327-638X","printIssn":"2327-0271","active":false,"publicationSubtype":{"id":5}},"seriesNumber":"892","title":"DOI/GTN-P climate and active-layer data acquired in the National Petroleum Reserve-Alaska and the Arctic National Wildlife Refuge","docAbstract":"This report provides data collected by the climate monitoring array of the U.S. Department of the Interior on Federal lands in Arctic Alaska over the period August 1998 to July 2013; this array is part of the Global Terrestrial Network for Permafrost, (DOI/GTN-P). In addition to presenting data, this report also describes monitoring, data collection, and quality-control methods. This array of 16 monitoring stations spans lat 68.5°N. to 70.5°N. and long 142.5°W. to 161°W., an area of approximately 150,000 square kilometers. Climate summaries are presented along with quality-controlled data. Data collection is ongoing and includes the following climate- and permafrost-related variables: air temperature, wind speed and direction, ground temperature, soil moisture, snow depth, rainfall totals, up- and downwelling shortwave radiation, and atmospheric pressure. These data were collected by the U.S. Geological Survey in close collaboration with the Bureau of Land Management and the U.S. Fish and Wildlife Service.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ds892","usgsCitation":"Urban, F.E., and Clow, G.D., 2014, DOI/GTN-P climate and active-layer data acquired in the National Petroleum Reserve-Alaska and the Arctic National Wildlife Refuge: U.S. Geological Survey Data Series 892, HTML Document, https://doi.org/10.3133/ds892.","productDescription":"HTML Document","onlineOnly":"Y","additionalOnlineFiles":"Y","temporalStart":"1998-01-01","temporalEnd":"2013-12-31","ipdsId":"IP-058477","costCenters":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"links":[{"id":318517,"rank":3,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/ds/0892/"},{"id":318516,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/ds/0892/introduction.html","text":"Report","size":"58 kB","linkFileType":{"id":5,"text":"html"}},{"id":318515,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/ds/0892/images/coverthb.jpg"}],"country":"United States","state":"Alaska","otherGeospatial":"Arctic National Wildlife Refuge, National Petroleum Reserve-Alaska","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -162.7294921875,\n 67.85898479324494\n ],\n [\n -162.7294921875,\n 71.44117085172385\n ],\n [\n -150.29296875,\n 71.44117085172385\n ],\n [\n -150.29296875,\n 67.85898479324494\n ],\n [\n -162.7294921875,\n 67.85898479324494\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -148.974609375,\n 66.65297740055279\n ],\n [\n -148.974609375,\n 70.24460360904779\n ],\n [\n -141.0205078125,\n 70.24460360904779\n ],\n [\n -141.0205078125,\n 66.65297740055279\n ],\n [\n -148.974609375,\n 66.65297740055279\n ]\n ]\n ]\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"548ac028e4b00f366bee37a4","contributors":{"authors":[{"text":"Urban, Frank E. 0000-0002-1329-1703 furban@usgs.gov","orcid":"https://orcid.org/0000-0002-1329-1703","contributorId":3129,"corporation":false,"usgs":true,"family":"Urban","given":"Frank","email":"furban@usgs.gov","middleInitial":"E.","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":false,"id":526978,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Clow, Gary D. 0000-0002-2262-3853 clow@usgs.gov","orcid":"https://orcid.org/0000-0002-2262-3853","contributorId":2066,"corporation":false,"usgs":true,"family":"Clow","given":"Gary","email":"clow@usgs.gov","middleInitial":"D.","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":526979,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70129575,"text":"fs20143107 - 2014 - The 3D Elevation Program: summary for Michigan","interactions":[],"lastModifiedDate":"2016-08-17T15:17:03","indexId":"fs20143107","displayToPublicDate":"2014-12-11T09:00:00","publicationYear":"2014","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":313,"text":"Fact Sheet","code":"FS","onlineIssn":"2327-6932","printIssn":"2327-6916","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2014-3107","title":"The 3D Elevation Program: summary for Michigan","docAbstract":"Elevation data are essential to a broad range of applications, including forest resources management, wildlife and habitat management, national security, recreation, and many others. For the State of Michigan, elevation data are critical for agriculture and precision farming, natural resources conservation, flood risk management, water supply and quality, infrastructure and construction management, coastal zone management, and other business uses. Today, high-density light detection and ranging (lidar) data are the primary sources for deriving elevation models and other datasets. Federal, State, Tribal, and local agencies work in partnership to (1) replace data that are older and of lower quality and (2) provide coverage where publicly accessible data do not exist. A joint goal of State and Federal partners is to acquire consistent, statewide coverage to support existing and emerging applications enabled by lidar data.
\nThe National Enhanced Elevation Assessment evaluated multiple elevation data acquisition options to determine the optimal data quality and data replacement cycle relative to cost to meet the identified requirements of the user community. The evaluation demonstrated that lidar acquisition at quality level 2 for the conterminous United States and quality level 5 interferometric synthetic aperture radar (ifsar) data for Alaska with a 6- to 10-year acquisition cycle provided the highest benefit/cost ratios. The 3D Elevation Program (3DEP) initiative selected an 8-year acquisition cycle for the respective quality levels. 3DEP, managed by the U.S. Geological Survey, the Office of Management and Budget Circular A–16 lead agency for terrestrial elevation data, responds to the growing need for high-quality topographic data and a wide range of other 3D representations of the Nation's natural and constructed features. The Michigan Statewide Authoritative Imagery and Lidar (MiSAIL) program provides statewide lidar coordination with local, State, and national groups in support of 3DEP for Michigan.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20143107","usgsCitation":"Carswell, W., 2014, The 3D Elevation Program: summary for Michigan (Originally posted December 10, 2014; Version 1.1: January 5, 2015; Version 1.2: June 29, 2015): U.S. Geological Survey Fact Sheet 2014-3107, 2 p., https://doi.org/10.3133/fs20143107.","productDescription":"2 p.","numberOfPages":"2","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-057034","costCenters":[{"id":423,"text":"National Geospatial Program","active":true,"usgs":true}],"links":[{"id":296601,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/fs20143107.jpg"},{"id":296600,"rank":3,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2014/3107/pdf/fs2014-3107.pdf","text":"Report","size":"351 KB","linkFileType":{"id":1,"text":"pdf"},"description":"Report"},{"id":296593,"rank":2,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/fs/2014/3107/"}],"country":"United States","state":"Michigan","geographicExtents":"{\"type\":\"FeatureCollection\",\"features\":[{\"type\":\"Feature\",\"geometry\":{\"type\":\"MultiPolygon\",\"coordinates\":[[[[-85.825955,45.404296],[-85.833516,45.378175],[-85.88301,45.443479],[-85.834891,45.428356],[-85.825955,45.404296]]],[[[-86.093536,45.007838],[-86.133655,44.996874],[-86.154824,45.002394],[-86.156689,45.010535],[-86.141644,45.040251],[-86.117908,45.048478],[-86.079103,45.030795],[-86.100315,45.02624],[-86.093536,45.007838]]],[[[-86.033174,45.15842],[-85.993194,45.152805],[-85.976803,45.138363],[-85.984095,45.087073],[-85.976883,45.06266],[-85.99736,45.055929],[-86.058653,45.100776],[-86.065016,45.140266],[-86.050473,45.158418],[-86.033174,45.15842]]],[[[-88.684434,48.115785],[-88.656915,48.139225],[-88.547033,48.174891],[-88.524753,48.165291],[-88.501088,48.168181],[-88.482039,48.179915],[-88.422601,48.190975],[-88.418244,48.18037],[-88.419875,48.170731],[-88.459697,48.158551],[-88.566938,48.093719],[-88.578053,48.084373],[-88.579784,48.058669],[-88.670073,48.011446],[-88.899184,47.9533],[-88.962664,47.923512],[-88.968903,47.901675],[-88.942387,47.895436],[-88.899698,47.902445],[-88.911665,47.891344],[-89.157738,47.824015],[-89.19017,47.831603],[-89.201812,47.850243],[-89.234533,47.851718],[-89.228507,47.858039],[-89.255202,47.876102],[-89.179154,47.93503],[-88.940886,48.01959],[-88.915032,48.020681],[-88.835714,48.056752],[-88.787556,48.063035],[-88.764256,48.085189],[-88.684434,48.115785]]],[[[-84.612845,45.834528],[-84.650783,45.85921],[-84.646876,45.884642],[-84.622515,45.87753],[-84.578328,45.820092],[-84.432472,45.786732],[-84.421267,45.792694],[-84.42159,45.805651],[-84.403208,45.784394],[-84.35602,45.771895],[-84.372248,45.745784],[-84.405852,45.722417],[-84.484128,45.73071],[-84.612845,45.834528]]],[[[-85.524448,45.829794],[-85.450206,45.796677],[-85.450206,45.776452],[-85.462581,45.765864],[-85.507263,45.778237],[-85.532009,45.798172],[-85.524448,45.829794]]],[[[-85.696872,45.69725],[-85.701809,45.736129],[-85.688849,45.747238],[-85.651866,45.743139],[-85.649353,45.722552],[-85.672187,45.696633],[-85.696872,45.69725]]],[[[-85.360952,45.817554],[-85.351434,45.795663],[-85.359048,45.776627],[-85.377132,45.769013],[-85.394264,45.778531],[-85.377132,45.812795],[-85.360952,45.817554]]],[[[-85.566441,45.760222],[-85.53562,45.750394],[-85.506133,45.754715],[-85.497656,45.746246],[-85.515145,45.749451],[-85.520803,45.737247],[-85.498777,45.726291],[-85.494016,45.698476],[-85.506104,45.681148],[-85.490252,45.652122],[-85.487026,45.621211],[-85.534064,45.578198],[-85.561634,45.572213],[-85.618049,45.582647],[-85.630016,45.598166],[-85.604521,45.639256],[-85.604881,45.681932],[-85.572309,45.711449],[-85.566441,45.760222]]],[[[-86.626187,45.573581],[-86.622023,45.55633],[-86.636895,45.542053],[-86.648792,45.543243],[-86.661284,45.574176],[-86.712328,45.610939],[-86.67727,45.613689],[-86.626187,45.573581]]],[[[-83.880387,41.720089],[-84.806082,41.696089],[-84.805883,41.760216],[-86.823628,41.76024],[-86.717037,41.819349],[-86.619442,41.893827],[-86.582197,41.942241],[-86.485223,42.118239],[-86.356218,42.254166],[-86.297168,42.358207],[-86.261573,42.443894],[-86.226037,42.592811],[-86.22905,42.637693],[-86.206834,42.719424],[-86.210737,42.859128],[-86.232707,43.015762],[-86.280756,43.136015],[-86.407832,43.338436],[-86.479276,43.515335],[-86.529507,43.593462],[-86.540916,43.633158],[-86.529686,43.676849],[-86.463436,43.744687],[-86.43114,43.815569],[-86.462756,43.969655],[-86.508827,44.032755],[-86.514704,44.057672],[-86.421576,44.128962],[-86.362847,44.208113],[-86.343793,44.249608],[-86.26871,44.345324],[-86.248083,44.420946],[-86.248914,44.483004],[-86.220697,44.566742],[-86.22545,44.59459],[-86.259029,44.663654],[-86.256796,44.686769],[-86.232482,44.70605],[-86.09074,44.740544],[-86.074658,44.766792],[-86.065966,44.821522],[-86.072468,44.884788],[-86.066745,44.905685],[-86.038332,44.915696],[-86.021513,44.902774],[-85.992535,44.900026],[-85.9316,44.968788],[-85.897626,44.962014],[-85.869852,44.939031],[-85.807403,44.949814],[-85.780439,44.977932],[-85.771395,45.015181],[-85.746444,45.051229],[-85.695715,45.076461],[-85.656024,45.145788],[-85.618639,45.186771],[-85.606963,45.178477],[-85.585986,45.180381],[-85.551072,45.210742],[-85.540497,45.210169],[-85.526734,45.189316],[-85.531461,45.177247],[-85.564897,45.153962],[-85.599801,45.149286],[-85.614319,45.127562],[-85.583198,45.071304],[-85.566066,45.059201],[-85.56613,45.043633],[-85.597181,45.040547],[-85.599652,45.021749],[-85.621878,45.004529],[-85.602356,44.974272],[-85.602034,44.926743],[-85.621403,44.923123],[-85.645456,44.883645],[-85.652355,44.849092],[-85.637,44.790078],[-85.640781,44.775561],[-85.627982,44.767508],[-85.593833,44.768651],[-85.581717,44.807784],[-85.532931,44.87319],[-85.530729,44.889182],[-85.559524,44.888113],[-85.564509,44.895246],[-85.533553,44.925762],[-85.520034,44.973996],[-85.475204,44.991053],[-85.464944,44.961062],[-85.48574,44.953626],[-85.500872,44.85883],[-85.555894,44.818256],[-85.57517,44.762766],[-85.554774,44.748917],[-85.527216,44.748235],[-85.504775,44.768082],[-85.509251,44.787334],[-85.499591,44.803838],[-85.462943,44.825044],[-85.3958,44.931018],[-85.378286,44.998587],[-85.380659,45.046319],[-85.366412,45.069023],[-85.366908,45.116938],[-85.386726,45.189497],[-85.388593,45.23524],[-85.371593,45.270834],[-85.307646,45.31314],[-85.262996,45.319507],[-85.196704,45.360641],[-85.143651,45.370369],[-85.032813,45.361251],[-84.91585,45.393115],[-84.912956,45.409776],[-84.922006,45.421914],[-84.990041,45.427618],[-84.978373,45.420171],[-85.040272,45.436509],[-85.087756,45.476335],[-85.115479,45.539406],[-85.119026,45.573002],[-85.07491,45.629242],[-85.007026,45.65636],[-84.942636,45.714292],[-84.951745,45.737326],[-85.011433,45.757962],[-85.00741,45.763168],[-84.805114,45.746378],[-84.781995,45.760345],[-84.7798,45.76965],[-84.79229,45.778464],[-84.780313,45.787224],[-84.734065,45.788205],[-84.715996,45.766174],[-84.573631,45.710381],[-84.46168,45.652404],[-84.442348,45.654771],[-84.427495,45.669201],[-84.376403,45.655565],[-84.329537,45.66438],[-84.215268,45.634767],[-84.128867,45.562284],[-84.122309,45.523788],[-84.095905,45.497298],[-84.056138,45.489349],[-84.028813,45.497225],[-83.939261,45.493189],[-83.909472,45.485784],[-83.806622,45.419159],[-83.721815,45.413304],[-83.599273,45.352561],[-83.570361,45.347198],[-83.538306,45.358167],[-83.514717,45.34646],[-83.488826,45.355872],[-83.422486,45.290989],[-83.381743,45.268983],[-83.41241,45.238905],[-83.363678,45.166469],[-83.316118,45.141958],[-83.30788,45.099093],[-83.265896,45.026844],[-83.340257,45.041545],[-83.36747,45.062268],[-83.399255,45.070364],[-83.433798,45.057616],[-83.453363,45.035331],[-83.446342,45.016655],[-83.431254,45.007998],[-83.450013,44.990219],[-83.433032,44.93289],[-83.404596,44.918761],[-83.39396,44.903056],[-83.320503,44.880571],[-83.321241,44.852962],[-83.300648,44.829831],[-83.296265,44.743502],[-83.274674,44.70477],[-83.287802,44.657703],[-83.31445,44.608926],[-83.308471,44.539902],[-83.326824,44.444411],[-83.321553,44.409119],[-83.333757,44.372486],[-83.332533,44.340464],[-83.343738,44.329763],[-83.373607,44.327784],[-83.414301,44.294543],[-83.425762,44.272487],[-83.442731,44.265361],[-83.460958,44.278176],[-83.500392,44.27661],[-83.53771,44.248171],[-83.567744,44.155899],[-83.573071,44.101298],[-83.591361,44.079237],[-83.58409,44.056748],[-83.650116,44.052404],[-83.679654,44.036365],[-83.687892,44.020709],[-83.680108,43.994196],[-83.76283,43.985361],[-83.82808,43.989003],[-83.877047,43.959351],[-83.890912,43.923314],[-83.907388,43.918062],[-83.916815,43.89905],[-83.929375,43.777091],[-83.945426,43.759946],[-83.954792,43.760932],[-83.939297,43.715369],[-83.909479,43.672622],[-83.852076,43.644922],[-83.770693,43.628691],[-83.769886,43.634924],[-83.725793,43.618691],[-83.703446,43.597646],[-83.669795,43.59079],[-83.553707,43.685432],[-83.540187,43.708746],[-83.515853,43.718157],[-83.506657,43.710907],[-83.48007,43.714636],[-83.470053,43.723418],[-83.440171,43.761694],[-83.446752,43.77186],[-83.438311,43.786846],[-83.411453,43.805033],[-83.407647,43.831998],[-83.33227,43.880522],[-83.331788,43.893901],[-83.347365,43.91216],[-83.30569,43.922489],[-83.28231,43.938031],[-83.26185,43.969021],[-83.227093,43.981003],[-83.058741,44.006224],[-83.024604,44.045174],[-82.990728,44.048846],[-82.967439,44.066138],[-82.915976,44.070503],[-82.889831,44.050952],[-82.793205,44.023247],[-82.783198,44.009366],[-82.746255,43.996037],[-82.678642,43.88373],[-82.65545,43.867883],[-82.643166,43.852468],[-82.647784,43.842684],[-82.633641,43.831224],[-82.612224,43.739771],[-82.597911,43.590016],[-82.539517,43.437539],[-82.523086,43.225361],[-82.486684,43.104688],[-82.415937,43.005555],[-82.42455,42.993393],[-82.412965,42.977041],[-82.455027,42.926866],[-82.469912,42.887459],[-82.468961,42.852314],[-82.482045,42.808629],[-82.467483,42.76191],[-82.510533,42.665172],[-82.518782,42.613888],[-82.589779,42.550678],[-82.640916,42.554973],[-82.686417,42.518597],[-82.664335,42.546244],[-82.680758,42.557909],[-82.688061,42.588417],[-82.701152,42.585991],[-82.713042,42.597904],[-82.683482,42.609433],[-82.690124,42.625033],[-82.669103,42.637225],[-82.645715,42.631145],[-82.630922,42.64211],[-82.623043,42.655951],[-82.630851,42.673341],[-82.700964,42.689548],[-82.813518,42.640833],[-82.819017,42.616333],[-82.789017,42.603434],[-82.782414,42.564834],[-82.834216,42.567849],[-82.874416,42.523535],[-82.883915,42.471836],[-82.870572,42.451235],[-82.894013,42.389437],[-82.915114,42.378137],[-82.928815,42.359437],[-82.92397,42.352068],[-83.064121,42.317738],[-83.096521,42.290138],[-83.128022,42.238839],[-83.133923,42.17474],[-83.121323,42.125742],[-83.133511,42.088143],[-83.157624,42.085542],[-83.188598,42.066431],[-83.181475,42.019301],[-83.187246,42.007573],[-83.208647,42.00504],[-83.216835,41.98862],[-83.248741,41.972735],[-83.269521,41.939042],[-83.292761,41.944616],[-83.315859,41.935893],[-83.341557,41.879956],[-83.366187,41.865505],[-83.379705,41.871729],[-83.40822,41.832654],[-83.436298,41.816471],[-83.443364,41.789118],[-83.42418,41.741042],[-83.503433,41.731547],[-83.880387,41.720089]]],[[[-88.116846,45.921703],[-88.189789,45.952208],[-88.209585,45.94428],[-88.239672,45.948982],[-88.249117,45.963663],[-88.292381,45.951115],[-88.316894,45.960969],[-88.326003,45.9553],[-88.334628,45.968808],[-88.380183,45.991654],[-88.414849,45.975483],[-88.458658,45.999391],[-88.492495,45.992157],[-88.509516,46.019169],[-88.565485,46.015708],[-88.589,46.005077],[-88.598093,46.017623],[-88.613063,45.990627],[-88.663697,45.989084],[-88.674606,46.010567],[-88.698716,46.017903],[-88.718397,46.013284],[-88.730675,46.026535],[-88.776187,46.015931],[-88.784411,46.032709],[-88.811948,46.021609],[-88.837991,46.030176],[-89.09163,46.138505],[-90.120489,46.336852],[-90.116844,46.355153],[-90.157851,46.409291],[-90.163422,46.434605],[-90.220532,46.503403],[-90.263018,46.502777],[-90.277131,46.524487],[-90.312581,46.517113],[-90.310329,46.536852],[-90.331887,46.553278],[-90.344338,46.552087],[-90.349462,46.53808],[-90.39332,46.532615],[-90.41562,46.563169],[-90.327626,46.607744],[-90.306609,46.602741],[-90.164026,46.645515],[-90.028392,46.67439],[-89.918466,46.740324],[-89.846962,46.796556],[-89.790663,46.818469],[-89.678469,46.832923],[-89.619329,46.81889],[-89.516895,46.841025],[-89.415154,46.843983],[-89.228362,46.912751],[-89.128698,46.992599],[-89.086742,46.985298],[-89.02893,47.00114],[-88.998907,46.99531],[-88.972802,47.002096],[-88.925586,47.040923],[-88.890708,47.099024],[-88.848176,47.115065],[-88.816684,47.139938],[-88.764351,47.155762],[-88.676624,47.216918],[-88.573997,47.245989],[-88.498756,47.295256],[-88.418841,47.371058],[-88.285635,47.422146],[-88.23944,47.429923],[-88.217822,47.448738],[-88.040291,47.475999],[-87.801184,47.473301],[-87.715942,47.439816],[-87.710471,47.4062],[-87.75138,47.405066],[-87.815371,47.38479],[-87.8567,47.395387],[-87.957058,47.38726],[-87.965598,47.368645],[-87.938787,47.346777],[-87.94336,47.335899],[-88.06009,47.295796],[-88.163059,47.216278],[-88.227552,47.199938],[-88.242109,47.172184],[-88.239487,47.151176],[-88.231797,47.149609],[-88.239895,47.139436],[-88.262537,47.145087],[-88.281652,47.138239],[-88.297547,47.098639],[-88.346501,47.079407],[-88.367624,47.019213],[-88.410157,46.978782],[-88.443901,46.972251],[-88.474217,46.889034],[-88.483748,46.831727],[-88.462349,46.786711],[-88.438427,46.786714],[-88.38141,46.838466],[-88.375577,46.857313],[-88.352145,46.857009],[-88.244437,46.929612],[-88.145561,46.966409],[-88.132957,46.962237],[-88.185964,46.920025],[-88.175197,46.90458],[-88.083937,46.920112],[-88.004298,46.906982],[-87.900695,46.909682],[-87.847037,46.884163],[-87.816794,46.891154],[-87.783216,46.879927],[-87.766243,46.861446],[-87.741857,46.865274],[-87.72588,46.827426],[-87.69459,46.827182],[-87.681561,46.842392],[-87.662261,46.815157],[-87.6333,46.812107],[-87.595307,46.78295],[-87.581674,46.729399],[-87.523308,46.688488],[-87.503238,46.647796],[-87.469023,46.635918],[-87.464108,46.614811],[-87.442612,46.602776],[-87.383961,46.59307],[-87.381649,46.580059],[-87.392974,46.572523],[-87.375613,46.54714],[-87.393985,46.533183],[-87.352448,46.501324],[-87.259116,46.488283],[-87.12744,46.494014],[-87.008724,46.532723],[-86.964534,46.516549],[-86.947077,46.472064],[-86.903742,46.466138],[-86.889094,46.458499],[-86.883919,46.441514],[-86.850111,46.434114],[-86.816026,46.437892],[-86.803557,46.466669],[-86.768516,46.479072],[-86.735929,46.475231],[-86.70323,46.439378],[-86.686412,46.454965],[-86.683819,46.498079],[-86.701929,46.511571],[-86.709325,46.543914],[-86.678182,46.561039],[-86.656479,46.558453],[-86.62738,46.53371],[-86.646393,46.485776],[-86.627441,46.47754],[-86.612173,46.493295],[-86.609039,46.470239],[-86.586168,46.463324],[-86.469306,46.551422],[-86.437167,46.54896],[-86.34989,46.578035],[-86.161681,46.669475],[-86.138295,46.672935],[-86.119862,46.657256],[-86.099843,46.654615],[-85.877908,46.690914],[-85.751345,46.67743],[-85.50951,46.675786],[-85.257999,46.753078],[-85.173042,46.763634],[-85.063556,46.757856],[-84.954009,46.771362],[-85.007616,46.728339],[-85.027513,46.697451],[-85.037056,46.600995],[-85.025491,46.546397],[-85.056133,46.52652],[-85.049847,46.503963],[-85.025598,46.483028],[-84.969464,46.47629],[-84.937145,46.489252],[-84.921931,46.469962],[-84.861448,46.46993],[-84.829491,46.444071],[-84.769151,46.453523],[-84.678423,46.487694],[-84.63102,46.484868],[-84.573522,46.427895],[-84.551496,46.418522],[-84.503719,46.43919],[-84.471848,46.434289],[-84.455527,46.453897],[-84.463322,46.467435],[-84.445149,46.489016],[-84.420274,46.501077],[-84.343599,46.507713],[-84.275814,46.492821],[-84.254434,46.500821],[-84.226131,46.53392],[-84.193729,46.53992],[-84.177428,46.52692],[-84.128925,46.530119],[-84.111225,46.504119],[-84.146172,46.41852],[-84.138906,46.372221],[-84.106247,46.321963],[-84.119629,46.315013],[-84.115563,46.268225],[-84.097766,46.256512],[-84.118175,46.233968],[-84.14595,46.224995],[-84.182732,46.23545],[-84.219494,46.231992],[-84.249164,46.206461],[-84.247687,46.17989],[-84.221001,46.163062],[-84.196669,46.16615],[-84.177298,46.183993],[-84.125022,46.180209],[-84.100126,46.15077],[-84.026536,46.131648],[-84.061329,46.113482],[-84.072398,46.09669],[-84.066257,46.087438],[-83.989526,46.032823],[-83.943933,46.031465],[-83.900535,45.998918],[-83.873147,45.993426],[-83.845399,46.025679],[-83.830146,46.022324],[-83.818202,46.002425],[-83.794055,45.995801],[-83.765277,46.018363],[-83.773785,46.051471],[-83.796555,46.056688],[-83.81252,46.073469],[-83.824036,46.103638],[-83.815826,46.108529],[-83.771821,46.090999],[-83.728165,46.090957],[-83.703861,46.103366],[-83.63498,46.103953],[-83.581315,46.089613],[-83.547202,46.047868],[-83.532913,46.011328],[-83.473946,45.988558],[-83.510623,45.929324],[-83.561838,45.912562],[-83.65766,45.945463],[-83.687695,45.935389],[-83.78611,45.933375],[-83.803332,45.943362],[-83.835505,45.941843],[-83.840869,45.952726],[-83.879616,45.966196],[-83.921257,45.958075],[-83.985141,45.967133],[-84.017565,45.959046],[-84.090391,45.967256],[-84.111174,45.978675],[-84.169368,45.966919],[-84.238174,45.967595],[-84.253993,45.956727],[-84.330346,45.956043],[-84.376429,45.931962],[-84.428239,45.958144],[-84.443086,45.977825],[-84.459956,45.970343],[-84.488536,45.98882],[-84.507201,45.991169],[-84.514071,45.971292],[-84.532392,45.969448],[-84.540995,46.019501],[-84.563891,46.032459],[-84.609063,46.026418],[-84.656567,46.052654],[-84.692735,46.027019],[-84.685254,45.973454],[-84.723039,45.967279],[-84.738849,45.945792],[-84.713614,45.920366],[-84.734002,45.907026],[-84.721277,45.873911],[-84.702122,45.853935],[-84.720609,45.848116],[-84.725734,45.837045],[-84.746985,45.835597],[-84.828996,45.871209],[-84.842147,45.898005],[-84.917288,45.930576],[-84.971232,45.984208],[-85.020951,46.012845],[-85.14516,46.050035],[-85.197523,46.044878],[-85.222416,46.060629],[-85.266385,46.065779],[-85.335466,46.092459],[-85.381263,46.082086],[-85.409463,46.100585],[-85.426916,46.101964],[-85.445835,46.086426],[-85.499422,46.09692],[-85.539479,46.080416],[-85.603785,46.030363],[-85.663966,45.967013],[-85.697203,45.960158],[-85.8092,45.979931],[-85.842404,45.965247],[-85.893196,45.967253],[-85.922737,45.948287],[-85.926017,45.932104],[-85.910264,45.922112],[-85.920581,45.920994],[-85.998868,45.950968],[-86.094753,45.966704],[-86.159415,45.953765],[-86.208255,45.962978],[-86.22906,45.94857],[-86.278007,45.942057],[-86.324232,45.90608],[-86.332625,45.851813],[-86.349134,45.83416],[-86.351658,45.798132],[-86.369918,45.789254],[-86.415971,45.793793],[-86.439661,45.760669],[-86.47905,45.757416],[-86.486028,45.746608],[-86.51457,45.752337],[-86.53328,45.710849],[-86.580936,45.71192],[-86.587528,45.666456],[-86.625132,45.663819],[-86.616893,45.606796],[-86.687208,45.634253],[-86.695275,45.648175],[-86.708038,45.649202],[-86.718191,45.67732],[-86.705184,45.690901],[-86.689102,45.687862],[-86.665677,45.702217],[-86.67148,45.72053],[-86.633138,45.747654],[-86.631018,45.782019],[-86.583391,45.778242],[-86.576858,45.801473],[-86.557215,45.808172],[-86.555186,45.831696],[-86.529208,45.853043],[-86.529573,45.874974],[-86.541464,45.890234],[-86.583304,45.898784],[-86.603293,45.876626],[-86.625736,45.868295],[-86.632478,45.843309],[-86.645998,45.833888],[-86.721113,45.845431],[-86.749638,45.867796],[-86.78208,45.860195],[-86.773279,45.811385],[-86.821523,45.770356],[-86.838658,45.741831],[-86.838746,45.722307],[-86.944158,45.695833],[-86.964275,45.672761],[-86.984588,45.705812],[-86.975224,45.75313],[-86.988438,45.810621],[-87.00508,45.831718],[-87.031435,45.837238],[-87.057439,45.812483],[-87.064302,45.758828],[-87.05555,45.751535],[-87.057444,45.736822],[-87.070442,45.718779],[-87.059953,45.708893],[-87.093365,45.701473],[-87.172241,45.661788],[-87.196852,45.636275],[-87.333407,45.446056],[-87.327749,45.425307],[-87.3925,45.369028],[-87.431684,45.316383],[-87.438908,45.293405],[-87.600796,45.146842],[-87.612019,45.123377],[-87.601086,45.104092],[-87.581969,45.097206],[-87.590208,45.095264],[-87.657135,45.107568],[-87.683902,45.144135],[-87.735135,45.171538],[-87.741805,45.197051],[-87.72796,45.207956],[-87.698248,45.281512],[-87.648126,45.339396],[-87.656624,45.367295],[-87.690281,45.389822],[-87.754104,45.349442],[-87.823028,45.35265],[-87.848368,45.340676],[-87.871204,45.360056],[-87.886949,45.35311],[-87.850969,45.401925],[-87.860432,45.423504],[-87.855298,45.441379],[-87.812976,45.464159],[-87.793447,45.498372],[-87.803364,45.537016],[-87.832296,45.558767],[-87.831689,45.568035],[-87.790874,45.564096],[-87.777671,45.609204],[-87.824676,45.653211],[-87.780808,45.680349],[-87.809075,45.699717],[-87.810144,45.71023],[-87.85548,45.726943],[-87.875813,45.753888],[-87.963452,45.75822],[-87.986429,45.769596],[-87.982617,45.782944],[-87.995876,45.795435],[-88.072091,45.780261],[-88.129461,45.809288],[-88.13611,45.819029],[-88.073134,45.871952],[-88.101814,45.883504],[-88.105677,45.904387],[-88.095354,45.913895],[-88.116846,45.921703]]]]},\"properties\":{\"name\":\"Michigan\",\"nation\":\"USA \"}}]}","edition":"Originally posted December 10, 2014; Version 1.1: January 5, 2015; Version 1.2: June 29, 2015","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"548ac02fe4b00f366bee37ac","contributors":{"authors":[{"text":"Carswell, William J. Jr. carswell@usgs.gov","contributorId":127609,"corporation":false,"usgs":true,"family":"Carswell","given":"William J.","suffix":"Jr.","email":"carswell@usgs.gov","affiliations":[{"id":423,"text":"National Geospatial Program","active":true,"usgs":true}],"preferred":false,"id":526945,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70128515,"text":"ds893 - 2014 - A 19-year record of chemical and isotopic composition of water from springs of the Shenandoah National Park, Virginia, 1995-2014","interactions":[],"lastModifiedDate":"2018-03-21T15:05:27","indexId":"ds893","displayToPublicDate":"2014-12-10T16:45:00","publicationYear":"2014","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":310,"text":"Data Series","code":"DS","onlineIssn":"2327-638X","printIssn":"2327-0271","active":false,"publicationSubtype":{"id":5}},"seriesNumber":"893","title":"A 19-year record of chemical and isotopic composition of water from springs of the Shenandoah National Park, Virginia, 1995-2014","docAbstract":"During October 1995 through March 2014, the U.S. Geological Survey in cooperation with the National Park Service, Luray, Virginia Station collected and analyzed samples of selected springs, air and unsaturated-zone gases in Shenandoah National Park, Virginia. The 19-year record of measurements of chemical and isotopic composition of water discharging from 34 springs located along the crest of the Blue Ridge Mountains in Shenandoah National Park, Virginia, is reported. These data include field measurements of water temperature, specific conductance, concentrations of dissolved oxygen (O2), and pH. Laboratory measurements included major-, minor-, and trace-element chemistry; concentrations of dissolved gases (nitrogen, [N2] argon [Ar], oxygen, and carbon dioxide [CO2]); concentrations of dissolved trace atmospheric gases, including trichlorofluoromethane (CFC-11), dichlorodifluoromethane (CFC-12), and trichlorotrifluoroethane (CFC-113) and sulfur hexafluoride (SF6); and hydrogen stable isotopic composition (δ2H) and oxygen isotopic composition (δ18O) of water. The data include an up to 14-year time series record of monthly sampling at five springs collected between 1995 and 2013. The measurements included temperature, specific conductance, pH, and discharge recorded at 30-minute intervals. Atmospheric mixing ratios of CFC-11, CFC-12, CFC-113, trifluorobromomethane (CF3Br), SF6, and trifluoromethyl sulfur pentafluoride (SF5CF3) in air from the Big Meadows Air Monitoring Station, Shenandoah National Park, were measured at approximately weekly intervals from September 1995 through March 2014.
\n\n
Additional data include monthly (between May 2001 and August 2003) measurements of temperature, N2, O2, Ar, CO2, CFC-12, CFC-11, CFC-113, and SF6 concentrations in unsaturated-zone air from seven multilevel piezometers in Shenandoah National Park and at the U.S. Geological Survey National Center in Reston, Virginia. All samples were analyzed at the U.S. Geological Survey Laboratories in Reston, Virginia.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ds893","collaboration":"Prepared in cooperation with National Park Service, Shenandoah National Park","usgsCitation":"Busenberg, E., Plummer, N., Coplen, T.B., Doughten, M.W., Widman, P.K., Casile, G.C., Wayland, J.E., and Nelms, D.L., 2014, A 19-year record of chemical and isotopic composition of water from springs of the Shenandoah National Park, Virginia, 1995-2014: U.S. Geological Survey Data Series 893, Report: vii, 11 p.; 23 Tables, https://doi.org/10.3133/ds893.","productDescription":"Report: vii, 11 p.; 23 Tables","numberOfPages":"22","onlineOnly":"Y","additionalOnlineFiles":"N","temporalEnd":"2014-03-31","ipdsId":"IP-042886","costCenters":[{"id":614,"text":"Virginia Water Science Center","active":true,"usgs":true}],"links":[{"id":296599,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ds893.jpg"},{"id":296597,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/ds/0893/pdf/ds893.pdf","text":"Report","size":"2.96 MB","linkFileType":{"id":1,"text":"pdf"}},{"id":296596,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/ds/0893/"},{"id":296598,"rank":3,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/ds/0893/downloads/23Tables.xlsx","size":"1.15 MB"}],"country":"United States","state":"Virginia","otherGeospatial":"Shenandoah National Park","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -79.51904296874999,\n 38.74551518488265\n ],\n [\n -78.321533203125,\n 38.736946065676\n ],\n [\n -78.42041015625,\n 37.996162679728116\n ],\n [\n -79.552001953125,\n 38.03078569382294\n ],\n [\n -79.51904296874999,\n 38.74551518488265\n ]\n ]\n ]\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"54896ea8e4b027aeab781276","contributors":{"authors":[{"text":"Busenberg, Eurybiades ebusenbe@usgs.gov","contributorId":2271,"corporation":false,"usgs":true,"family":"Busenberg","given":"Eurybiades","email":"ebusenbe@usgs.gov","affiliations":[{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true}],"preferred":true,"id":519721,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Plummer, Niel 0000-0002-4020-1013 nplummer@usgs.gov","orcid":"https://orcid.org/0000-0002-4020-1013","contributorId":190100,"corporation":false,"usgs":true,"family":"Plummer","given":"Niel","email":"nplummer@usgs.gov","affiliations":[{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true}],"preferred":true,"id":519719,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Coplen, Tyler B. 0000-0003-4884-6008 tbcoplen@usgs.gov","orcid":"https://orcid.org/0000-0003-4884-6008","contributorId":508,"corporation":false,"usgs":true,"family":"Coplen","given":"Tyler","email":"tbcoplen@usgs.gov","middleInitial":"B.","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":27111,"text":"National Water Quality Program","active":true,"usgs":true},{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true},{"id":37464,"text":"WMA - Laboratory & Analytical Services Division","active":true,"usgs":true}],"preferred":true,"id":519718,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Doughten, Michael W. doughten@usgs.gov","contributorId":4717,"corporation":false,"usgs":true,"family":"Doughten","given":"Michael","email":"doughten@usgs.gov","middleInitial":"W.","affiliations":[{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true}],"preferred":true,"id":519725,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Widman, Peggy K. pkwidman@usgs.gov","contributorId":4009,"corporation":false,"usgs":true,"family":"Widman","given":"Peggy","email":"pkwidman@usgs.gov","middleInitial":"K.","affiliations":[{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true}],"preferred":true,"id":519724,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Casile, Gerolamo C. jcasile@usgs.gov","contributorId":4007,"corporation":false,"usgs":true,"family":"Casile","given":"Gerolamo","email":"jcasile@usgs.gov","middleInitial":"C.","affiliations":[{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true}],"preferred":true,"id":519722,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Wayland, Julian E. jwayland@usgs.gov","contributorId":4008,"corporation":false,"usgs":true,"family":"Wayland","given":"Julian","email":"jwayland@usgs.gov","middleInitial":"E.","affiliations":[{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true}],"preferred":true,"id":519723,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Nelms, David L. 0000-0001-5747-642X dlnelms@usgs.gov","orcid":"https://orcid.org/0000-0001-5747-642X","contributorId":1892,"corporation":false,"usgs":true,"family":"Nelms","given":"David","email":"dlnelms@usgs.gov","middleInitial":"L.","affiliations":[{"id":37759,"text":"VA/WV Water Science Center","active":true,"usgs":true},{"id":614,"text":"Virginia Water Science Center","active":true,"usgs":true}],"preferred":true,"id":519720,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70135184,"text":"sir20145211 - 2014 - Methods for estimating magnitude and frequency of floods in Arizona, developed with unregulated and rural peak-flow data through water year 2010","interactions":[],"lastModifiedDate":"2014-12-10T13:28:26","indexId":"sir20145211","displayToPublicDate":"2014-12-10T14:15:00","publicationYear":"2014","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2014-5211","title":"Methods for estimating magnitude and frequency of floods in Arizona, developed with unregulated and rural peak-flow data through water year 2010","docAbstract":"Flooding is among the worst natural disasters responsible for loss of life and property in Arizona, underscoring the importance of accurate estimation of flood magnitude for proper structural design and floodplain mapping. Twenty-four years of additional peak-flow data have been recorded since the last comprehensive regional flood frequency analysis conducted in Arizona. Periodically, flood frequency estimates and regional regression equations must be revised to maintain the accurate estimation of flood frequency and magnitude.
\n\n
Annual peak-flow data collected through water year 2010 were compiled from 448 unregulated streamflow-gaging stations, hereafter referred to as streamgages, in Arizona having a minimum of 10 years of record. Flood frequency estimates were first computed with station (or at-site) skew using the Expected Moments Algorithm with a multiple Grubbs-Beck test to identify multiple potentially influential low flows to fit a Pearson Type III distribution. Next, a multiple step Bayesian least-squares-regression approach was used to determine a new statewide regional skew of −0.09. No basin characteristics analyzed were statistically significant in explaining the variation in skew and as a result, the constant model was chosen as the best regional skew model for the Arizona study area. The mean square error used in Bulletin 17B (B17B) of the Interagency Advisory Committee on Water Data is used to describe the precision of the regional skew. The constant model had a mean square error equal to 0.08, which corresponds to an effective record length of 85 years. This is a marked improvement over a previous Arizona regional skew analysis, with a reported mean square error of 0.31, for a corresponding effective record length of around 17 years. Thus the new regional model had almost five times the information content (as measured by effective record length) of that calculated in USGS Water Supply Paper 2433, published in 1997, or the value of 0.302 reported in the B17B generalized skew map. The flood frequency estimates were recalculated using a weighted skew of the station and regional skew. Station flood frequency estimates for each streamgage are presented for the 50-, 20-, 10-, 4-, 2-, 1-, 0.5-, and 0.2-percent annual exceedance probabilities.
\n\n
Geographical information systems were used to compute basin characteristic information for each streamgage for the purpose of developing regional equations to estimate flood statistics at ungaged basins. Five hydrologic flood regions in Arizona were defined in a multivariate regionalization process based on mean basin elevation, mean annual precipitation, and soil permeability. A regional generalized least-squares-regression analysis was used to develop five sets of equations from 344 nonredundant streamgages, corresponding to five regions, for estimating the 50-, 20-, 10-, 4-, 2-, 1-, 0.5-, and 0.2-percent annual exceedance probabilities at ungaged basins in Arizona. The regression equations developed for these five regions were based on one or more of the statistically significant explanatory variables: drainage area, mean basin elevation, and mean annual precipitation. Average standard errors of prediction for the regression regions for the five regions ranged from 27 to 122 percent and the pseudo-coefficients of determination (pseudo-R2), a measure of the proportion of peak-flow variation that is explained by the basin characteristics, ranged from 68 to 98 percent. Regression equations for Central Highlands (region 4) had the lowest model error and the greatest pseudo-R2 metrics. The equations for Colorado Plateau (region 2) regression equations generally had greater model error and lower pseudo-R2 metrics. The improvement of regional regression equation model error and pseudo-R2 metrics was related to higher numbers of streamgages, longer period of record, and even spatial coverage within a region.
\n\n
The regional regression equations were integrated into the U.S. Geological Survey’s StreamStats program. The StreamStats program is a national map-based web application that allows the public to easily access published flood frequency and basin characteristic statistics. The interactive web application allows a user to select a point within a watershed (gaged or ungaged) and retrieve flood-frequency estimates derived from the current regional regression equations and geographic information system data within the selected basin. StreamStats provides users with an efficient and accurate means for retrieving the most up to date flood frequency and basin characteristic data. StreamStats is intended to provide consistent statistics, minimize user error, and reduce the need for large datasets and costly geographic information system software.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20145211","collaboration":"Prepared in cooperation with the Flood Control Districts of Maricopa County, Pima County, Pinal County, Yavapai County, Mohave County, Cochise County, Navajo County, Greenlee County, and Salt River Project, U.S. Forest Service, and Bureau of Reclamation.","usgsCitation":"Paretti, N., Kennedy, J.R., Turney, L.A., and Veilleux, A.G., 2014, Methods for estimating magnitude and frequency of floods in Arizona, developed with unregulated and rural peak-flow data through water year 2010: U.S. Geological Survey Scientific Investigations Report 2014-5211, Report: vii, 61 p.; 16 Tables, https://doi.org/10.3133/sir20145211.","productDescription":"Report: vii, 61 p.; 16 Tables","numberOfPages":"73","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-040579","costCenters":[{"id":128,"text":"Arizona Water Science Center","active":true,"usgs":true}],"links":[{"id":296591,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir20145211.gif"},{"id":296589,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2014/5211/downloads/sir2014-5211.pdf","text":"Report","size":"3.9 MB","linkFileType":{"id":1,"text":"pdf"}},{"id":296590,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/sir/2014/5211/downloads/SIR2014-5211_tables.xlsx","text":"Tables","size":"650 kB"},{"id":296585,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2014/5211/"}],"country":"United States","state":"Arizona","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -109.00634765625,\n 37.055177106660814\n ],\n [\n -108.984375,\n 31.31610138349565\n ],\n [\n -111.1376953125,\n 31.259769987394286\n ],\n [\n -114.98291015625,\n 32.47269502206151\n ],\n [\n -114.873046875,\n 36.19109202182454\n ],\n [\n -114.14794921875,\n 37.020098201368114\n ],\n [\n -109.00634765625,\n 37.055177106660814\n ]\n ]\n ]\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"54896eb5e4b027aeab781282","contributors":{"authors":[{"text":"Paretti, Nicholas V. nparetti@usgs.gov","contributorId":802,"corporation":false,"usgs":true,"family":"Paretti","given":"Nicholas V.","email":"nparetti@usgs.gov","affiliations":[{"id":128,"text":"Arizona Water Science Center","active":true,"usgs":true}],"preferred":false,"id":526927,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kennedy, Jeffrey R. 0000-0002-3365-6589 jkennedy@usgs.gov","orcid":"https://orcid.org/0000-0002-3365-6589","contributorId":2172,"corporation":false,"usgs":true,"family":"Kennedy","given":"Jeffrey","email":"jkennedy@usgs.gov","middleInitial":"R.","affiliations":[{"id":128,"text":"Arizona Water Science Center","active":true,"usgs":true}],"preferred":true,"id":526928,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Turney, Lovina A. labbott@usgs.gov","contributorId":5744,"corporation":false,"usgs":true,"family":"Turney","given":"Lovina","email":"labbott@usgs.gov","middleInitial":"A.","affiliations":[],"preferred":true,"id":526929,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Veilleux, Andrea G. aveilleux@usgs.gov","contributorId":4404,"corporation":false,"usgs":true,"family":"Veilleux","given":"Andrea","email":"aveilleux@usgs.gov","middleInitial":"G.","affiliations":[{"id":502,"text":"Office of Surface Water","active":true,"usgs":true}],"preferred":true,"id":526930,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70116948,"text":"sir20145121 - 2014 - Evaluation of the magnitude and frequency of floods in urban watersheds in Phoenix and Tucson, Arizona","interactions":[],"lastModifiedDate":"2014-12-10T12:56:36","indexId":"sir20145121","displayToPublicDate":"2014-12-10T13:45:00","publicationYear":"2014","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2014-5121","title":"Evaluation of the magnitude and frequency of floods in urban watersheds in Phoenix and Tucson, Arizona","docAbstract":"Flooding in urban areas routinely causes severe damage to property and often results in loss of life. To investigate the effect of urbanization on the magnitude and frequency of flood peaks, a flood frequency analysis was carried out using data from urbanized streamgaging stations in Phoenix and Tucson, Arizona. Flood peaks at each station were predicted using the log-Pearson Type III distribution, fitted using the expected moments algorithm and the multiple Grubbs-Beck low outlier test. The station estimates were then compared to flood peaks estimated by rural-regression equations for Arizona, and to flood peaks adjusted for urbanization using a previously developed procedure for adjusting U.S. Geological Survey rural regression peak discharges in an urban setting. Only smaller, more common flood peaks at the 50-, 20-, 10-, and 4-percent annual exceedance probabilities (AEPs) demonstrate any increase in magnitude as a result of urbanization; the 1-, 0.5-, and 0.2-percent AEP flood estimates are predicted without bias by the rural-regression equations. Percent imperviousness was determined not to account for the difference in estimated flood peaks between stations, either when adjusting the rural-regression equations or when deriving urban-regression equations to predict flood peaks directly from basin characteristics. Comparison with urban adjustment equations indicates that flood peaks are systematically overestimated if the rural-regression-estimated flood peaks are adjusted upward to account for urbanization. At nearly every streamgaging station in the analysis, adjusted rural-regression estimates were greater than the estimates derived using station data. One likely reason for the lack of increase in flood peaks with urbanization is the presence of significant stormwater retention and detention structures within the watershed used in the study.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20145121","collaboration":"Prepared in cooperation with the Flood Control District of Maricopa County.","usgsCitation":"Kennedy, J.R., and Paretti, N., 2014, Evaluation of the magnitude and frequency of floods in urban watersheds in Phoenix and Tucson, Arizona: U.S. Geological Survey Scientific Investigations Report 2014-5121, v, 29 p., https://doi.org/10.3133/sir20145121.","productDescription":"v, 29 p.","numberOfPages":"39","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-037882","costCenters":[{"id":128,"text":"Arizona Water Science Center","active":true,"usgs":true}],"links":[{"id":296584,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir20145121.gif"},{"id":296583,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2014/5121/downloads/sir2014-5121.pdf","text":"Report","size":"6.2 MB","linkFileType":{"id":1,"text":"pdf"}},{"id":296582,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2014/5121/"}],"country":"United States","state":"Arizona","city":"Phoenix, Tucson","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -109.00634765625,\n 37.055177106660814\n ],\n [\n -108.984375,\n 31.31610138349565\n ],\n [\n -111.1376953125,\n 31.259769987394286\n ],\n [\n -114.98291015625,\n 32.47269502206151\n ],\n [\n -114.873046875,\n 36.19109202182454\n ],\n [\n -114.14794921875,\n 37.020098201368114\n ],\n [\n -109.00634765625,\n 37.055177106660814\n ]\n ]\n ]\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"54896eb3e4b027aeab78127a","contributors":{"authors":[{"text":"Kennedy, Jeffrey R. 0000-0002-3365-6589 jkennedy@usgs.gov","orcid":"https://orcid.org/0000-0002-3365-6589","contributorId":2172,"corporation":false,"usgs":true,"family":"Kennedy","given":"Jeffrey","email":"jkennedy@usgs.gov","middleInitial":"R.","affiliations":[{"id":128,"text":"Arizona Water Science Center","active":true,"usgs":true}],"preferred":true,"id":519059,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Paretti, Nicholas V. nparetti@usgs.gov","contributorId":802,"corporation":false,"usgs":true,"family":"Paretti","given":"Nicholas V.","email":"nparetti@usgs.gov","affiliations":[{"id":128,"text":"Arizona Water Science Center","active":true,"usgs":true}],"preferred":false,"id":519058,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70135156,"text":"70135156 - 2014 - Predicting spatial and temporal distribution of Indo-Pacific lionfish (Pterois volitans) in Biscayne Bay through habitat suitability modeling","interactions":[],"lastModifiedDate":"2016-11-22T18:40:45","indexId":"70135156","displayToPublicDate":"2014-12-10T12:00:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1018,"text":"Biological Invasions","active":true,"publicationSubtype":{"id":10}},"title":"Predicting spatial and temporal distribution of Indo-Pacific lionfish (Pterois volitans) in Biscayne Bay through habitat suitability modeling","docAbstract":"Invasive species may exhibit higher levels of growth and reproduction when environmental conditions are most suitable, and thus their effects on native fauna may be intensified. Understanding potential impacts of these species, especially in the nascent stages of a biological invasion, requires critical information concerning spatial and temporal distributions of habitat suitability. Using empirically supported environmental variables (e.g., temperature, salinity, dissolved oxygen, rugosity, and benthic substrate), our models predicted habitat suitability for the invasive lionfish (Pterois volitans) in Biscayne Bay, Florida. The use of Geographic Information Systems (GIS) as a platform for the modeling process allowed us to quantify correlations between temporal (seasonal) fluctuations in the above variables and the spatial distribution of five discrete habitat quality classes, whose ranges are supported by statistical deviations from the apparent best conditions described in prior studies. Analysis of the resulting models revealed little fluctuation in spatial extent of the five habitat classes on a monthly basis. Class 5, which represented the area with environmental variables closest to the best conditions for lionfish, occupied approximately one-third of Biscayne Bay, with subsequent habitats declining in area. A key finding from this study was that habitat suitability increased eastward from the coastline, where higher quality habitats were adjacent to the Atlantic Ocean and displayed marine levels of ambient water quality. Corroboration of the models with sightings from the USGS-NAS database appeared to support our findings by nesting 79 % of values within habitat class 5; however, field testing (i.e., lionfish surveys) is necessary to confirm the relationship between habitat classes and lionfish distribution.
","language":"English","publisher":"Springer","doi":"10.1007/s10530-014-0819-6","usgsCitation":"Bernal, N.A., DeAngelis, D., Schofield, P.J., and Sullivan Sealey, K., 2014, Predicting spatial and temporal distribution of Indo-Pacific lionfish (Pterois volitans) in Biscayne Bay through habitat suitability modeling: Biological Invasions, v. 17, no. 6, p. 1603-1614, https://doi.org/10.1007/s10530-014-0819-6.","productDescription":"12 p.","startPage":"1603","endPage":"1614","numberOfPages":"12","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-051582","costCenters":[{"id":566,"text":"Southeast Ecological Science Center","active":true,"usgs":true}],"links":[{"id":296572,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Florida","otherGeospatial":"Biscayne Bay","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -80.42816162109375,\n 25.23972731233395\n ],\n [\n -80.42816162109375,\n 25.888878582127084\n ],\n [\n -80.013427734375,\n 25.888878582127084\n ],\n [\n -80.013427734375,\n 25.23972731233395\n ],\n [\n -80.42816162109375,\n 25.23972731233395\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"17","issue":"6","noUsgsAuthors":false,"publicationDate":"2014-12-05","publicationStatus":"PW","scienceBaseUri":"54896eb5e4b027aeab781284","contributors":{"authors":[{"text":"Bernal, Nicholas A.","contributorId":127809,"corporation":false,"usgs":false,"family":"Bernal","given":"Nicholas","email":"","middleInitial":"A.","affiliations":[{"id":7162,"text":"University of Miami, Coral Gables, FL","active":true,"usgs":false}],"preferred":false,"id":526911,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"DeAngelis, Donald L. 0000-0002-1570-4057 don_deangelis@usgs.gov","orcid":"https://orcid.org/0000-0002-1570-4057","contributorId":2860,"corporation":false,"usgs":true,"family":"DeAngelis","given":"Donald L.","email":"don_deangelis@usgs.gov","affiliations":[{"id":566,"text":"Southeast Ecological Science Center","active":true,"usgs":true}],"preferred":false,"id":526912,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Schofield, Pamela J. 0000-0002-8752-2797 pschofield@usgs.gov","orcid":"https://orcid.org/0000-0002-8752-2797","contributorId":917,"corporation":false,"usgs":true,"family":"Schofield","given":"Pamela","email":"pschofield@usgs.gov","middleInitial":"J.","affiliations":[{"id":566,"text":"Southeast Ecological Science Center","active":true,"usgs":true}],"preferred":false,"id":526913,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Sullivan Sealey, Kathleen","contributorId":127810,"corporation":false,"usgs":false,"family":"Sullivan Sealey","given":"Kathleen","email":"","affiliations":[{"id":5112,"text":"University of Miami","active":true,"usgs":false}],"preferred":false,"id":526914,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70133618,"text":"ofr20141233 - 2014 - Quality-assurance and data-management plan for water-quality activities in the Kansas Water Science Center, 2014","interactions":[],"lastModifiedDate":"2014-12-10T10:16:31","indexId":"ofr20141233","displayToPublicDate":"2014-12-10T11:00:00","publicationYear":"2014","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2014-1233","title":"Quality-assurance and data-management plan for water-quality activities in the Kansas Water Science Center, 2014","docAbstract":"As the Nation’s largest water, earth, and biological science and civilian mapping information agency, the U.S. Geological Survey is relied on to collect high-quality data, and produce factual and impartial interpretive reports. This quality-assurance and data-management plan provides guidance for water-quality activities conducted by the Kansas Water Science Center. Policies and procedures are documented for activities related to planning, collecting, storing, documenting, tracking, verifying, approving, archiving, and disseminating water-quality data. The policies and procedures described in this plan complement quality-assurance plans for continuous water-quality monitoring, surface-water, and groundwater activities in Kansas.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20141233","usgsCitation":"Rasmussen, T.J., Bennett, T.J., Foster, G., Graham, J.L., and Putnam, J.E., 2014, Quality-assurance and data-management plan for water-quality activities in the Kansas Water Science Center, 2014: U.S. Geological Survey Open-File Report 2014-1233, vii, 41 p., https://doi.org/10.3133/ofr20141233.","productDescription":"vii, 41 p.","numberOfPages":"53","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-052134","costCenters":[{"id":353,"text":"Kansas Water Science Center","active":false,"usgs":true}],"links":[{"id":296570,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr20141233.jpg"},{"id":296568,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2014/1233/"},{"id":296569,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2014/1233/pdf/of2014-1233.pdf","size":"824 kB","linkFileType":{"id":1,"text":"pdf"}}],"country":"United States","state":"Kansas","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -102.0849609375,\n 40.07807142745009\n ],\n [\n -94.52636718749999,\n 40.06125658140474\n ],\n [\n -94.6142578125,\n 36.949891786813296\n ],\n [\n -102.15087890624999,\n 36.98500309285596\n ],\n [\n -102.0849609375,\n 40.07807142745009\n ]\n ]\n ]\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"54896eb6e4b027aeab781286","contributors":{"authors":[{"text":"Rasmussen, Teresa J. 0000-0002-7023-3868 rasmuss@usgs.gov","orcid":"https://orcid.org/0000-0002-7023-3868","contributorId":3336,"corporation":false,"usgs":true,"family":"Rasmussen","given":"Teresa","email":"rasmuss@usgs.gov","middleInitial":"J.","affiliations":[{"id":353,"text":"Kansas Water Science Center","active":false,"usgs":true}],"preferred":true,"id":526898,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bennett, Trudy J. trudyben@usgs.gov","contributorId":4218,"corporation":false,"usgs":true,"family":"Bennett","given":"Trudy","email":"trudyben@usgs.gov","middleInitial":"J.","affiliations":[{"id":353,"text":"Kansas Water Science Center","active":false,"usgs":true}],"preferred":false,"id":526899,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Foster, Guy M. gfoster@usgs.gov","contributorId":3437,"corporation":false,"usgs":true,"family":"Foster","given":"Guy M.","email":"gfoster@usgs.gov","affiliations":[{"id":353,"text":"Kansas Water Science Center","active":false,"usgs":true}],"preferred":false,"id":526900,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Graham, Jennifer L. 0000-0002-6420-9335 jlgraham@usgs.gov","orcid":"https://orcid.org/0000-0002-6420-9335","contributorId":1769,"corporation":false,"usgs":true,"family":"Graham","given":"Jennifer","email":"jlgraham@usgs.gov","middleInitial":"L.","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"preferred":true,"id":526901,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Putnam, James E. jputnam@usgs.gov","contributorId":2021,"corporation":false,"usgs":true,"family":"Putnam","given":"James","email":"jputnam@usgs.gov","middleInitial":"E.","affiliations":[{"id":353,"text":"Kansas Water Science Center","active":false,"usgs":true}],"preferred":false,"id":526902,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70134346,"text":"sir20145221 - 2014 - Hydrogeologic framework and groundwater/surface-water interactions of the South Fork Nooksack River Basin, northwestern Washington","interactions":[],"lastModifiedDate":"2014-12-10T09:26:48","indexId":"sir20145221","displayToPublicDate":"2014-12-10T10:15:00","publicationYear":"2014","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2014-5221","title":"Hydrogeologic framework and groundwater/surface-water interactions of the South Fork Nooksack River Basin, northwestern Washington","docAbstract":"A hydrogeologic framework of the South Fork (SF) Nooksack River Basin in northwestern Washington was developed and hydrologic data were collected to characterize the groundwater-flow system and its interaction with surface‑water features. In addition to domestic, agricultural, and commercial uses of groundwater within the SF Nooksack River Basin, groundwater has the potential to provide ecological benefits by maintaining late-summer streamflows and buffering stream temperatures. Cold-water refugia, created and maintained in part by groundwater, have been identified by water-resource managers as key elements to restore the health and viability of threatened salmonids in the SF Nooksack River. The SF Nooksack River drains a 183-square mile area of the North Cascades and the Puget Lowland underlain by unconsolidated glacial and alluvial sediments deposited over older sedimentary, metamorphic, and igneous bedrock. The primary aquifer that interacts with the SF Nooksack River was mapped within unconsolidated glacial outwash and alluvial sediment. The lower extent of this unit is bounded by bedrock and fine-grained, poorly sorted unconsolidated glaciomarine and glaciolacustrine sediments. In places, these deposits overlie and confine an aquifer within older glacial sediments. The extent and thickness of the hydrogeologic units were assembled from mapped geologic units and lithostratigraphic logs of field-inventoried wells. Generalized groundwater-flow directions within the surficial aquifer were interpreted from groundwater levels measured in August 2012; and groundwater seepage gains and losses to the SF Nooksack River were calculated from synoptic streamflow measurements made in the SF Nooksack River and its tributaries in September 2012. A subset of the field-inventoried wells was measured at a monthly interval to determine seasonal fluctuations in groundwater levels during water year 2013. Taken together, these data provide the foundation for a future groundwater-flow model of the SF Nooksack River Basin that may be used to investigate the potential effects of future climate change, land use, and groundwater pumping on water resources in the study area. Site-specific hydrologic data, including time series of longitudinal temperature profiles measured with a fiber-optic distributed temperature sensor and continuous monitoring of stream stage and water levels measured in wells in adjacent wetlands and aquifers, also were measured to characterize the interaction among the SF Nooksack River, surficial aquifers, and riparian wetlands.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20145221","collaboration":"Prepared in cooperation with the Nooksack Indian Tribe","usgsCitation":"Gendaszek, A.S., 2014, Hydrogeologic framework and groundwater/surface-water interactions of the South Fork Nooksack River Basin, northwestern Washington: U.S. Geological Survey Scientific Investigations Report 2014-5221, Report: vi, 36 p.; 2 Plates: 20.04 x 14.65 inches and 29.76 x 15 inches, https://doi.org/10.3133/sir20145221.","productDescription":"Report: vi, 36 p.; 2 Plates: 20.04 x 14.65 inches and 29.76 x 15 inches","numberOfPages":"46","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-059387","costCenters":[{"id":622,"text":"Washington Water Science Center","active":true,"usgs":true}],"links":[{"id":296559,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir20145221.jpg"},{"id":296556,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2014/5221/pdf/sir2014-5221.pdf","size":"5.9 MB","linkFileType":{"id":1,"text":"pdf"}},{"id":296557,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/sir/2014/5221/downloads/sir2014-5221_plate1.pdf","text":"Plate 1","size":"1.1 MB","linkFileType":{"id":1,"text":"pdf"}},{"id":296558,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/sir/2014/5221/downloads/sir2014-5221_plate2.pdf","text":"Plate 2","size":"1.0 MB","linkFileType":{"id":1,"text":"pdf"}},{"id":296553,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2014/5221/"}],"country":"United States","state":"Washington","otherGeospatial":"South Fork Noooksack River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -121.640625,\n 48.58932584966972\n ],\n [\n -121.6845703125,\n 48.09275716032736\n ],\n [\n -120.38818359375,\n 48.09275716032736\n ],\n [\n -120.43212890625,\n 48.58932584966972\n ],\n [\n -121.640625,\n 48.58932584966972\n ]\n ]\n ]\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"54896eb4e4b027aeab78127e","contributors":{"authors":[{"text":"Gendaszek, Andrew S. 0000-0002-2373-8986 agendasz@usgs.gov","orcid":"https://orcid.org/0000-0002-2373-8986","contributorId":3509,"corporation":false,"usgs":true,"family":"Gendaszek","given":"Andrew","email":"agendasz@usgs.gov","middleInitial":"S.","affiliations":[{"id":622,"text":"Washington Water Science Center","active":true,"usgs":true}],"preferred":true,"id":526863,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ]}